PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Zastosowanie H-rozkładów i rozkładów macierzowo-wykładniczych do modelowania zakłóceń radiolokacyjnych

Autorzy
Identyfikatory
Warianty tytułu
EN
Radar clutter modelling using H-distributions and matrix-exponential distributions
Języki publikacji
PL
Abstrakty
PL
W pracy zaproponowano dwie niezależne zaawansowane matematycznie metody opisu zakłóceń radiolokacyjnych i analizy systemów radiolokacyjnych z uwzględnieniem wpływu tych zakłóceń. Pierwsza z nich wynika ze spostrzeżenia, że powszechnie stosowane modele zakłóceń są opisywane tzw. H-rozkładami i można do ich analizy wykorzystać teorię H-funkcji Foxa. Druga z metod polega na zastosowaniu rozkładów macierzowo-wykładniczych (rozkładów ME), a w szczególności pewnej ich podklasy, a mianowicie rozkładów typu fazowego (rozkładów PH). Podejście to pozwala na stosowanie stosunkowo prostej algebry macierzowej do analizy wpływu zakłóceń. Na wstępie omówiono zasadę działania radaru impulsowego, podstawy statystycznej teorii detekcji i optymalną strukturę detektora, a także nowoczesne metody realizacji bloku przetwarzania sygnałów radiolokacyjnych. Przedstawiono klasyfikację rozkładów zakłóceń, ze szczególnym podkreśleniem roli tzw. rozkładów złożonych. Znane z literatury podejścia do rozkładów złożonych usystematyzowano i uporządkowano. Pokazano, że niemal wszystkie znane w literaturze rozkłady zakłóceń są przypadkami szczególnymi lub granicznymi tzw. uogólnionego rozkładu złożonego, a wiele z nich sprowadza się do jednego z tych przypadków szczególnych, a mianowicie do uogólnionego rozkładu gamma. Oba te rozkłady dokładnie przebadano dzięki potraktowaniu ich jako H-rozkłady. Wyprowadzono nieznane dotąd w probabilistyce jawne wzory na gęstość, dystrybuantę, momenty i transformatę Laplace' a gęstości dla wielu najważniejszych rozkładów amplitudy i mocy zakłóceń radiolokacyjnych. Dla wszystkich badanych rozkładów zaproponowano wspólną parametryzację, dzięki czemu możliwe stało się pokazanie w innym świetle znanych i odkrycie nowych związków między tymi rozkładami. Wiele miejsca poświęcono analizie asymptotycznych właściwości funkcji gęstości prawdopodobieństwa rozkładów amplitudy i mocy zakłóceń radiolokacyjnych. Zaproponowano zastosowanie teorii wartości ekstremalnych (Gumbela) do formalizacji właściwości tzw. ogona rozkładu. Zauważono związek gęstości uogólnionego rozkładu złożonego ze znaną z matematyki całką Faxena. Znaleziono nowe, prostsze od znanych dotąd, pełne rozwinięcie asymptotyczne tej całki w nieskończoności. Dzięki temu pokazano, że dowolny uogólniony rozkład złożony zachowuje się asymptotycznie identycznie jak uogólniony rozkład gamma, czyli należy do rozkładów typu I w klasyfikacji Gumbela. Z kolei wyprowadzenie pełnego rozwinięcia w zerze całki Faxena pozwoliło na znalezienie istotnych błędów w znanych do tej pory w literaturze przedstawieniach gęstości uogólnionego rozkładu złożonego w postaci szeregów nieskończonych. W dalszej części pracy przedstawiono pojęcie rozkładu macierzowo-wykładniczego i jego reprezentacji, a następnie omówiono najważniejsze właściwości takiego rozkładu znane z literatury. Podano nową metodę wyznaczania reprezentacji rozkładu ME na podstawie momentów za pomocą algorytmu QD Rutishausera. Zaproponowano nowatorską koncepcję połączenia teorii rozkładów kołowo symetrycznych i teorii rozkładów typu fazowego. W ramach tej koncepcji wyprowadzono nieznane dotąd wzory na funkcję charakterystyczną (wyrażającą się przez transformatę Hankela) rozkładu kołowo symetrycznego zmiennej losowej, której amplituda lub moc ma rozkład PH. Podano przykłady dowodzące efektywności algebraizacji obliczeń probabilistycznych związanych z rozkładami zakłóceń, możliwej dzięki zastosowaniu rozkładów typu fazowego. Przedstawiono także metodę dokładnej analizy rozkładów prawdopodobieństwa z uwzględnieniem kwantowania, za pomocą dyskretnych rozkładów typu fazowego, opartą na podanej w pracy reprezentacji PH słusznej dla dowolnego rozkładu dyskretnego. Wykorzystując teorię łańcuchów Markowa zaproponowano ujednolicone podejście do ciągłych i dyskretnych rozkładów PH przez ich reprezentacje grafami przepływu sygnału. Dla obu klas rozkładów podano nowe algorytmy otrzymywania takich grafów bezpośrednio na podstawie reprezentacji macierzowej rozkładu, z uwzględnieniem nietrywialnego wektora prawdopodobieństw początkowych. W skazano sposób wyznaczania funkcji charakterystycznej rozkładu (albo L-transformaty gęstości czy Z-transformaty funkcji prawdopodobieństwa) jako transmitancji tak otrzymanego grafu. Dzięki temu podejściu znaleziono interesujący związek między rozkładami ciągłymi i dyskretnymi typu fazowego przez przybliżenie Eulera (transformację FD). W zakończeniu rozprawy wskazano na możliwe kierunki dalszych badań i potencjalne obszary zastosowań uzyskanych wyników.
EN
In the monograph there are proposed two independent advanced mathematical methods for the radar clutter modeling and for the analysis of radar systems including the influence of the clutter. The first one is based on the observation that most commonly used radar clutter distributions belong to the class of the so-called H-distributions. Such distributions can be analyzed by using the theory of Fox H-functions. The other method utilizes matrix-exponential (ME) distributions, and especially their most important proper subset, namely phase-type (PH) distributions. This approach results in a simplified analysis of the influence of the clutter, due to a straightforward matrix algebra. The introductory chapters provide basic background concerning the principles of pulsed radar and statistical theory of optimal detection. The modern techniques for the implementation of the radar processors are also described. A detailed classification of radar clutter distributions is presented, with a special emphasis put on the role of compound distributions. Most approaches to the compound distributions known in the literature are compared and generalized. It is shown that almost all widely used clutter distributions are special or limiting cases of the Generalized Compound (GC) distribution. Furthermore, most of them can be regarded as one particular special case, namely the Generalized Gamma (Gr) distribution. Both GC and Gr distributions are thoroughly analyzed by treating them as H -distributions. The novel closed-form formulas for the density, distribution function, moments and the Laplace transform of the density are derived for a number of most popular radar clutter distributions. All investigated distributions share the common parameterization, which makes it possible to show some new relationships between these distributions. A significant part of the monograph is devoted to the asymptotic analysis of the densities of the amplitude and intensity of the radar clutter. The application of Gumbel's Extreme Values Theory (EVT) is proposed to formalize the properties of the tail of distributions. The author has found a close relationship between the density of the GC distribution and the Faxen integral. Due to the derivation of a new, closed-form, full asymptotic expansion of the Faxen integral at infinity it was shown that the tail of the GC distribution is the same as that of the Gr distribution, i.e., it belongs to the Type I distributions by Gumbel. The closed-form full asymptotic expansion of the Faxen integral at the origin was also derived, which made it evident that infinite series representations for the GC den sity known in the literature are erroneous. Regarding the second approach, the definition, basic properties and matrix representations of ME distributions are described, based on the available literature. The new method is given for computing the matrix representation based on the moments. This method utilizes a variant of the QD algorithm by Rutishauser. Anovel approach to Spherically Invariant Random Vectors (SIRV) via phase-type distributions is also proposed. New formulas based on the Hankel transform are derived for the characteristic function of the SIRV distribution, provided that the corresponding amplitude or intensity is PH-distributed. A number of examples are given that illustrate the advantages of the phase-type approach to the analysis of radar clutter distributions in radar systems. Moreover, the method for the exact analysis of probability distributions in digital systems, taking into account the quantization effects, is proposed. The method utilizes discrete PH distributions based on the representation of the arbitrary discrete distribution presented in the monograph. A unified approach to continuous and discrete PH distributions via signal flow graphs is proposed, based on the Markov chain theory. The algorithms for obtaining such graphs directly from the corresponding matrix representations are derived for both continuous and discrete PH distributions. The non-trivial initial probability vectors are allowed. The characteristic function (or L-transform of the density, or Z-transform of the probability function) can be computed as the transfer function of the graph, using the Mason rule. The unified approach resulted in obtaining an interesting relationship between continuous and discrete PH distributions via Euler's approximation (also known as the FD transformation). In the concluding section of the monograph, the directions for the future research and some potential application areas are pointed out.
Rocznik
Tom
Strony
5--273
Opis fizyczny
Bibliogr. 351, schem., wykr.
Twórcy
autor
  • Instytut Systemów Elektronicznych Politechnika Warszawska
Bibliografia
  • [1] Aalen O. O., Gjessing H. K.: Understanding the shape of the hazard rate: a process point of view. Statistical Science, 16(1):1-22, 2001.
  • [2] Aalo V. A., Piboongungon T., Iskander C.-D.: Bit-error rate of binary digital modulation schemes in generalized gamma fading channels. IEEE Communications Letters, 9(2):139-141, luty 2005.
  • [3] Abate J., Choudhury G. L., Whitt W.: On the Laguerre method for numerically inverting Laplace transforms. INFORMS Journal on Computing, 8(4):413-427, 1996.
  • [4] Abate J., Whitt W.: The Fourier-series method for inverting transforms of probability distributions. Queueing Systems, 10(1):5-88, 1992.
  • [5] Abate J., Whitt W.: Computing Laplace transforms for numerical inversion via continued fractions. INFORMS Journal on Computing, 11(4):394-405, 1999.
  • [6] Abdi A., Hashemi H., Nader-Esfahani S.: On the PDF of the sum of random vectors. IEEE Transactions on Communications, 48(1):7-12, styczeń 2000.
  • [7] Abdi A., Kaveh M.: K distribution: an appropriate substitute for Rayleigh-lognormal distribution in fading-shadowing wireless channels. Electronics Letters, 34(9):851-852, 30 kwiecień 1998.
  • [8] Abraham D. A.: Efficacy analysis of the power-law detector for non-Rayleigh distributed reverberation in active sonar systems. Proceedings IEEE Aerospace Conference, tom 4, strony 4/1739-4/1748, 10-17 marzec 2001.
  • [9] Abraham D. A., Lyons A. P.: Novel physical interpretations of K-distributed reverberation. IEEE Journal of Oceanic Engineering, 27(4):800-813, październik 2002.
  • [10] Abraham D. A., Lyons A. P: Simulation of non-Rayleigh reverberation and clutter. IEEE Journal of Oceanic Engineering, 29(2):347-362, kwiecień 2004.
  • [11] Abramowitz M., Stegun I. A., redaktorzy: Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Numer 55 serii Applied Mathematics Series. National Bureau of Standards, Washington, D. C., grudzień 1972. Tenth printing.
  • [12] Adamski M., Kulpa K., Nałęcz M., Wojtkiewicz A.: Phase noise in two-dimensional spectrum of video signal in FMCW homodyne radar. Proceedings of the XIII International Conference on Microwaves, Radar and Wireless Communications MIKON-2000, tom 2, strony 645-648, Wrocław (Poland), 22-24 maj 2000.
  • [13] Al-Hussaini E. K.: Performance of the greater-of and censored greater-of detectors in multiple target environments. IEE Proceedings Pt. F - Comm. Radar Signal Processing, 135(3):193-198, czerwiec 1988.
  • [14] Al-Musallam F. A., Tuan V. K.: H-function with complex parameters, I: Existence. Internat. J. Math. Math. Sci., 25(9):571-586, marzec 2001.
  • [15] Aldous D., Shepp L.: The least variable phase type distribution is Erlang. Comm. Statist. Stochastic Models, 3(3):467-473, 1987.
  • [16] Aloisio V., Di Vito A., Galati G.: An optimal detector for moderately fluctuating targets. Proc. International Conference RADAR 92, strony 110-113, Brighton (UK), 12-13 październik 1992.
  • [17] Amindavar H., Ritcey J. A.: Padé approximations of probability density functions. IEEE Transactions on Aerospace and Electronic Systems, 30(2):416-424, kwiecień 1994.
  • [18] Amindavar H., Ritcey J. A.: Padé approximations for detectability in K-clutter and noise. IEEE Transactions on Aerospace and Electronic Systems, 30(2):425-434, kwiecień 1994.
  • [19] Amoroso L.: Ricerche intorno alla curva dei redditi. Annali di Mat., 4(2):123-155, 1925.
  • [20] Anastassopoulos V., Lampropoulos G. A.: A generalized compound model for radar clutter. Proc. of the 1994 IEEE National Radar Conference, strony 41-45, Atlanta, 29-31 marzec 1994.
  • [21] Anastassopoulos V., Lampropoulos G. A., Drosopoulos A., Rey M.: High resolution radar clutter statistics. IEEE Transactions on Aerospace and Electronic Systems, 35(1):43-60, styczeń 1999.
  • [22] Asmussen S.: Phase-type distributions and related point processes: Fitting and recent advances. Chakravarty S. R., Alfa A. S., redaktorzy, Matrix-Analytic Methods in Stochastic Models, tom 183 serii Lecture Notes in Pure and Appl. Math., strony 137-149. Marcel Dekker, New York, 1997.
  • [23] Asmussen S.: Matrix-analytic models and their analysis. Scand. J. Statist., 27(2):193-226, czerwiec 2000.
  • [24] Asmussen S., Bladt M.: Renewal theory and queueing algorithms for matrix-exponential distributions. Chakravarty S. R., Alfa A. S., redaktorzy, Matrix-Analytic Methods in Stochastic Models, tom 183 serii Lecture Notes in Pure and Appl. Math., strony 313-341. Marcel Dekker, New York, 1997.
  • [25] Baker G. A. Jr., Graves-Morris P.: Padé approximants, tom 59 serii Encyclopedia of Mathematics and its Applications. Cambridge University Press, Cambridge, 1996.
  • [26] Bakhoom N. G.: Asymptotic expansions of the function Fk(x) = [wzór funkcji]. Proc. London Math. Soc. (2), 35:83-100, 1933.
  • [27] Banerjee A., Burlina R, Chellappa R.: Adaptive target detection in foliage-penetrating SAR images using alpha-stable models. IEEE Transactions on Image Processing, 8(12):1823-1831, grudzień 1999.
  • [28] Barrios J. A., Betancor J. J.: A Kratzel's integral transformation of distributions. Collect. Math., 42(1): 11-32, 1991.
  • [29] Barrios J. A., Betancor J. J.: On asymptotic expansions of Kratzel's integral transforms. Portugaliae Mathematica, 49(2):205-232, 1992.
  • [30] Bertrand J., Bertrand R, Ovarlez J.-R: The Mellin transform. Poularikas A. D., redaktor, The Transforms and Applications Handbook: Second Edition, rozdział 11. CRC Press, Boca Raton, 2000.
  • [31] Betancor J. J., Barrios J. A.: A real inversion formula for the Kratzel's generalized Laplace transform. Extracta Math., 6(2):55-57, 1991.
  • [32] Billingsley J. B.: Low Angle Radar Land Clutter: Measurements and Empirical Models. William Andrew, Norwich (NY, USA), 2002.
  • [33] Billingsley J. B., Farina A., Gini F., Greco M. V., Verrazzani L.: Statistical analyses of measured radar ground clutter data. IEEE Transactions on Aerospace and Electronic Systems, 35(2):579-593, kwiecień 1999.
  • [34] Blacknell D.: Comparison of parameter estimators for K-distribution. IEE Proceedings Pt. F - Radar, Sonar and Navigation, 141(1):45-52, luty 1994.
  • [35] Blacknell D.: New method for the simulation of correlated K-distributed clutter. IEE Proceedings Pt. F - Radar, Sonar and Navigation, 141(1):53-58, luty 1994.
  • [36] Bladt M., Neuts M. F.: Matrix-exponential distributions: Calculus and interpretations via flows. Stochastic Models, 19(1):113-124, 2003.
  • [37] Blake I. F., Thomas J. B.: On a class of processes arising in linear estimation theory. IEEE Transactions on Information Theory, 14(1):12-16, styczeń 1968.
  • [38] Blasch E. R, Hensel M.: Fusion of distributions for radar clutter modeling. Proceedings of the Seventh International Conference on Information Fusion, strony 629-636, Stockholm (Sweden), 28 czerwiec - 1 lipiec 2004.
  • [39] Bleistein N., Handelsman R. A.: Asymptotic Expansions of Integrals. Dover Publications, Inc., New York, 1986. Pełny poprawiony przedruk. Oryginalne wydanie: Holt, Rinehart and Winston, New York, 1975.
  • [40] Bleistein N., Handelsman R. A., Lew J. S.: Functions whose Fourier transforms decay at infinity: An extension of the Riemann-Lebesgue lemma. SIAM J. Math. Anal., 3(3):485-495, 1972.
  • [41] Bobbio A., Horváth A., Scarpa M., Telek M.: Acyclic discrete phase type distributions: properties and a parameter estimation algorithm. Performance Evaluation, 54(1):1-32, wrzesień 2003.
  • [42] Bobbio A., Horváth A., Telek M.: The scale factor: a new degree of freedom in phase-type approximation. Performance Evaluation, 56(1-4):121-144, marzec 2004.
  • [43] Bobbio A., Horváth A., Telek M.: Matching three moments with minimal acyclic phase type distributions. Stochastic Models, 21(2-3):303-326, 2005.
  • [44] Bobbio A., Telek M.: A benchmark for PH estimation algorithms: Results for acyclic-PH. Comm. Statist. Stochastic Models, 10(3):661-677, 1994.
  • [45] Boersma J.: A function arising in one-dimensional percolation. SIAM Rev., 38(4):671-675, grudzień 1996.
  • [46] Bohnenkamp H., Haverkort B.: The mean value of the maximum. Hermanns E., Segala R., redaktorzy, Process Algebra and Probabilistic Methods, tom 2399 serii Lecture Notes in Comput. Sci., strony 37-56. Springer, Berlin, styczeń 2002.
  • [47] Boyer J. M.: Simple constant amortized time generation of fixed length numeric partitions. J. Algorithms, 54(1):31-39, 2005.
  • [48] Braaksma B. L. J.: Asymptotic expansions and analytic continuations for a class of Barnes-integrals. Compos. Math., 15(3):239-341, 1963.
  • [49] Buderi R.: Radar: Wynalazek, który zmienił świat. Prószyński i S-ka, Warszawa, 2006.
  • [50] Buschman R. G.: The asymptotic expansion of an integral. Rendiconti di Matematica, Serie VI, 7:481-186, 1974.
  • [51] Butler R. W.: Reliabilities for feedback systems and their saddlepoint approximation. Statistical Science, 15(3):279-298, 2000.
  • [52] Butler R. W., Huzurbazar A. V.: Stochastic network models for survival analysis. Journal of the American Statistical Association, 92(437):246-257, marzec 1997.
  • [53] Butler R. W., Huzurbazar A. V.: Bayesian prediction of waiting times in Stochastic models. The Canadian Journal of Statistics, 28(2):311-325, 2000.
  • [54] Cabaña A., Quiroz A. J.: Using the empirical moment generating function in testing for the Weibull and the type I extreme value distributions. Technical Report 2001-05, Centro de Estadística y Software Matemático, Universidad Simón Bolívar, Caracas (Venezuela), 2001.
  • [55] Candel S. M.: Dual algorithms for fast calculation of the Fourier-Bessel transform. IEEE Transactions on Acoustics, Speech and Signal Processing, 29(5):963-972, październik 1981.
  • [56] Carter B. D., Springer M. D.: The distribution of products, quotients and powers of independent H-function variates. SIAM J. Appl. Math., 33(4):542-558, grudzień 1977.
  • [57] Castillo E.: Extreme value theory in engineering. Statistical Modeling and Decision Science. Academic Press Inc., Boston, (MA, USA), 1988.
  • [58] Castillo E., Hadi A. S., Balakrishnan N., Sarabia J. M.: Extreme value and related models with applications in engineering and science. Wiley Series in Probability and Statistics. Wiley-Interscience [John Wiley & Sons], Hoboken, (NJ, USA), 2005.
  • [59] Cathey W. T.: Optyczne przetwarzanie informacji i holografia. PWN, Warszawa, 1978.
  • [60] Chaudhry M. A.: Transformation of the extended gamma function [wzór funkcji] with applications to astrophysical thermonuclear functions. Astrophysics and Space Science, 262(3):263-270, wrzesień 1998.
  • [61] Chaudhry M. A., Zubair S. M.: Extended incomplete gamma functions with applications. J. Math. Anal. Appl., 274(2):725-745, 2002.
  • [62] Chaudhry M. A., Zubair S. M.: On a Class of Incomplete Gamma Functions with Applications. Chapman & Hall/CRC, Boca Raton, 2002.
  • [63] Chen W.-K.: Applied graph theory. Graphs and electrical networks. North-Holland, Amsterdam, wydanie drugie, 1976.
  • [64] Cheng J., Tellambura C., Beaulieu N. C.: Performance of digital linear modulations on Weibull slow-fading channels. IEEE Transactions on Communications, 52(8):1265-1268, sierpień 2004.
  • [65] Chitroub S., Houacine A., Sansal B.: Statistical characterization and modeling of SAR images. Signal Processing, 82:69-92, 2003.
  • [66] Chua L. O., Lin P.-M.: Computer-aided analysis of electronic circuits. Algorithms and computational techniques. Prentice-Hall, Englewood Cliffs, 1975.
  • [67] Ciardo G., Miner A. S.: SMART: Stochastic Model Checking Analyzer for Reliability and Timing. Version 1.1. University of California, Riverside, Department of Computer Science and Engineering, Riverside (CA, USA), 2006.
  • [68] Colzani L., Crespi A., Travaglini G., Vignati M.: Equiconvergence theorems for Fourier-Bessel expansions with applications to the harmonic analysis of radial functions in Euclidean and non-Euclidean spaces. Trans. Amer. Math. Soc., 338(1):43-55, 1993.
  • [69] Comtet L.: Advanced Combinatorics. The Art of Finite and Infinite Expansions. D. Reidel Publ. Co., Dordrecht (Holland), wydanie poprawione i uzupełnione, 1974.
  • [70] Constantine A. G., Robinson N. L: The Weibull renewal function for moderate to large arguments. Compul. Statist. Data Anal, 24(1):9-27, 1997.
  • [71] Conte E., De Maio A.: Mitigation techniques for non-Gaussian sea clutter. IEEE Journal of Oceanic Engineering, 29(2):284-302, kwiecień 2004.
  • [72] Conte E., De Maio A., Galdi C.: Signal detection in compound-Gaussian noise: Neyman-Pearson and CFAR detectors. IEEE Transactions on Signal Processing, 48(2):419-428, luty 2000.
  • [73] Conte E., Di Bisceglie M., Longo M., Lops M.: Canonical detection in spherically invariant noise. IEEE Transactions on Communications, 43(2/3/4):347-353, luty/marzec/kwiecień 1995.
  • [74] Conte E., Longo M.: Characterization of radar clutter as a spherically invariant random process. IEE Proceedings Pt. F - Comm. Radar Signal Processing, 134(2):191-197, kwiecień 1987.
  • [75] Cowper M.: Nonlinear processing of non-Gaussian stochastic and chaotic deterministic time series. Praca doktorska, The University of Edinburgh, marzec 2000.
  • [76] Cramblitt R. M., Parker K. J.: Generation of non-Rayleigh speckle distributions using marked regularity models. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 46(4):867-874, lipiec 1999.
  • [77] Cruz-Báez D. L, Rodríguez J.: The [wzór]-transformation on McBride's spaces of generalized functions. Comment. Math. Univ. Carolinae, 39(3):445-452, 1998.
  • [78] Cruz-Báez D. L, Rodríguez J. E.: New inversion formulas for the Krätzel transformation. Int. J. Math. Math. Sci., 25(4):253-263, 2001.
  • [79] Czekała Z.: Parada radarów. Dom Wydawniczy Bellona, Warszawa, 1999.
  • [80] Davidson G., Griffiths H. D., Ablett S.: Statistical analysis of high resolution land clutter. Proceedings of the RADAR 2002 Conference, strony 434-438, Edinburgh (UK), 15-17 październik 2002.
  • [81] Delignon Y., Fjørtoft R., Pieczynski W.: Compound distribution for radar images. Proc. Scandinavian Conference on Image Analysis, SCIA'2001, strony 741-748, Bergen (Norway), 11-14 czerwiec 2001.
  • [82] Delignon Y., Garello R., Hillion A.: Statistical modelling of ocean SAR images. IEE Proceedings Pt. F - Radar, Sonar and Navigation, 144(6):348-354, grudzień 1997.
  • [83] Delignon Y., Pieczynski W.: Modeling non-Rayleigh speckle ditribution in SAR images. IEEE Transactions on Geoscience and Remote Sensing, 40(6):1430-1435, czerwiec 2002.
  • [84] Denny M., Greig D.: Modelling sea clutter for airborne pulse-Doppler radar. Low Grazing Angle Clutter: Its Characterization, Measurement and Application, strony 37-1-37-11. NATO Research and Technology Organization, październik 2000. Proc. of the RTO Sensors and Electronics Technology Panel (SET) Symposium, held in Laurel (MD, USA), 25-27 April 2000.
  • [85] Deo N.: Graph theory with applications to engineering and computer science. Prentice-Hall, Englewood Cliffs, 1974.
  • [86] Devroye L.: Non-Uniform Random Variate Generation. Springer, New York, 1986.
  • [87] DiCiccio T. J.: Approximate inference for the generalized gamma distribution. Technometrics, 29(1):33-40, luty 1987.
  • [88] Dingle N. J., Harrison P. G., Knottenbelt W. J.: Uniformization and hypergraph partitioning for the distributed computation of response time in very large Markov models. Journal of Parallel and Distributed Computing, 64(8):908-920, sierpień 2004.
  • [89] Drumheller D. M.: Padé approximations to matched filter amplitude probability functions. IEEE Transactions on Aerospace and Electronic Systems, 35(3):1033-1045, lipiec 1999.
  • [90] Drumheller D. M., Lew H.: Padé approximations to Rician statistical functions. IEEE Transactions on Aerospace and Electronic Systems, 35(4):1421-1428, październik 1999.
  • [91] Drumheller D. M., Lew H.: Padé approximations to matched-filter amplitude probability functions: Rayleigh mixtures and multiple observations. IEEE Transactions on Aerospace and Electronic Systems, 38(2):621-632, kwiecień 2002.
  • [92] Eadie W. T., Drijad D., James F. E., Roos M., Sadoulet B.: Metody statystyczne w fizyce doświadczalnej. PWN, Warszawa, 1989.
  • [93] Erdélyi A., redaktor: Higher Transcendental Functions, tom 3. Mc Graw-Hill, New York, 1955.
  • [94] Fabijonas B. R.: Laplace's method on a computer algebra system with an application to the real valued modified Bessel functions. J. Comput. Appl. Math., 146(2):323-342, 2002.
  • [95] Fackrell M. W.: Characterization of Matrix-exponential Distributions. Praca doktorska, School of Applied Mathematics, The University of Adelaide, 18 listopad 2003.
  • [96] Falk M., Hüsler J., Reiss R.-D.: Laws of small numbers: extremes and rare events, tom 23 serii DMV Seminar. Birkhauser Verlag, Basel, 1994.
  • [97] Farina A., Gini F., Greco M. V., Verrazzani L.: High resolution sea clutter data: statistical analysis of recorded live data. IEE Proceedings Pt. F - Radar, Sonar and Navigation, 144(3):121-130, czerwiec 1997.
  • [98] Faxen H.: Expansion in series of the integral [wzór]. Arkiv för Matematik, Astronomi och Fysik, 15(13):1-57, 1921.
  • [99] Feldmann A., Whitt W.: Fitting mixtures of exponentials to long-tail distributions to analyze network performance models. Performance Evaluation, 31(3-4):245-279, styczeń 1998.
  • [100] Feller W.: Wstęp do rachunku prawdopodobieństwa, tom I. PWN, Warszawa, wydanie piąte, 1987.
  • [101] Feller W.: Wstęp do rachunku prawdopodobieństwa, tom II. PWN, Warszawa, wydanie drugie poprawione, 1978.
  • [102] Frery A. C., Müller H. -J., Yanasse C. C. F., Sant'Anna S. J. S.: A model for extremely heterogeneous clutter. IEEE Transactions on Geoscience and Remote Sensing, 35(3):648-659, maj 1997.
  • [103] Galati G., redaktor: Advanced radar techniques and systems, tom 4 serii IEE Radar, Sonar, Navigation and Avionics Series. Peter Peregrinus Ltd., London, 1993.
  • [104] Gandhi P. P, Kassam S. A.: Analysis of CFAR processors in nonhomogeneous back-ground. IEEE Transactions on Aerospace and Electronic Systems, 24(4):427-445, lipiec 1988.
  • [105] Гантмахер Ф. П.: Теория матриц. Наука, Москва, 1988. Издание четвертое, дополненное.
  • [106] Gilbert J. R., Moler C., Schreiber R.: Sparse matrices in MATLAB: design and implementation. SIAM J. Matrix Anal. Appl, 13(1):333-356, 1992.
  • [107] Gini F., Farina A.: Vector subspace detection in compound-Gaussian clutter. Part I: Survey and new results. IEEE Transactions on Aerospace and Electronic Systems, 38(4):1295-1311, październik 2002.
  • [108] Gini F., Farina A., Montanari M.: Vector subspace detection in compound-Gaussian clutter. Part II: Performance analysis. IEEE Transactions on Aerospace and Electronic Systems, 38(4):1312-1323, październik 2002.
  • [109] Gnedenko B.: Sur la distribution limite du terme maximum d'une série aléatoire. Annals of Mathematics. Second Series, 44(3):423-453, lipiec 1943.
  • [110] Goldman J.: Detection in the presence of spherically symmetric random vectors. IEEE Transactions on Information Theory, 22(1):52-59, styczeń 1976.
  • [111] Golub G. H., Van Loan C. F: Matrix computations. Johns Hopkins Studies in the Mathematical Sciences. Johns Hopkins University Press, Baltimore (MD, USA), 1996.
  • [112] Gordon S. D., Ritcey J. A.: Likelihood detection for nonfluctuating targets in ergodic K-clutter. Record of the IEEE 1995 International Radar Conference, strony 668-673, 8-11 maj 1995.
  • [113] Gorenflo R., Luchko Yu., Mainardi F.: Analytical properties and applications of the Wright function. Fract. Calc. Appl. Anal., 2(4):383-414, 1999.
  • [114] Gotwols B. L., Chapman R. D., Sterner R. E. II: Ocean radar backscatter statistics and the generalized log normal distribution. Kong J. A., redaktor, Proc. PIERS, Boston (MA, USA), 12 lipiec 1994. CD-ROM.
  • [115] Graham R. L., Knuth D. E., Patashnik O.: Matematyka konkretna. PWN, Warszawa, 1996.
  • [116] Gray R. M., Neuhoff D. L.: Quantization. IEEE Transactions on Information Theory, 44(6):2325-2383, październik 1998.
  • [117] Greco M., Bordoni F, Gini F.: X-band sea-clutter nonstationarity: Influence of long waves. IEEE Journal of Oceanic Engineering, 29(2):269-283, kwiecień 2004.
  • [118] Griffiths H. D., Fassi C., Dunsmore M. R. B., Ablett S., Walbridge M. R.: Statistical analysis of high resolution land clutter. Low Grazing Angle Clutter: Its Characterization, Measurement and Application, strony 25-1--25-10. NATO Research and Technology Organization, październik 2000. Proc. of the RTO Sensors and Electronics Technology Panel (SET) Symposium, held in Laurel (MD, USA), 25-27 April 2000.
  • [119] Gumbel E. J.: Statistics of Extremes. Columbia University Press, New York, 1958.
  • [120] Guo D., DiCesare F., Zhou M.: A moment generating function approach for evaluating extended stochastic Petri nets. IEEE Transactions on Automatic Control, 38(2):321-327, luty 1993.
  • [121] Guo J.: Approximations of gamma function and psi function and their applications in sediment transport. Proc. 13th IAHR-APD Congress, tom 1, strony 219-223, Singapore, 2002. International Association for Hydraulic Engineering and Research, Asia and Pacific Division.
  • [122] Gut A.: On the moment problem. Bernoulli, 8(3):407-421, 2002.
  • [123] Hansen V. G., Sawyer J. H.: Detectability loss due to greatest of selection in a cell-averaging CFAR. IEEE Transactions on Aerospace and Electronic Systems,16(1):115-118, styczeń 1980.
  • [124] Harrison P. G.: Laplace transform inversion and passage-time distributions in Markov processes. Journal of Applied Probability, 27(1):74-87, 1990.
  • [125] Haubold H. J., Mathai A. M.: An integral arising frequently in astronomy and physics. SIAM Rev., 40(4):995-997, grudzień 1998.
  • [126] Hawkes C., Haykin S.: Modeling of clutter for coherent pulsed radar. IEEE Transactions on Information Theory, 21(6):703-707, listopad 1975.
  • [127] Haykin S., Bakker R., Currie B.: Uncovering nonlinear dynamics - the case study of sea clutter. Proceedings of the IEEE, 90(5):860-881, maj 2002.
  • [128] Hegyi S.: Multiplicity distributions in strong interactions: a generalized negative binomial model. Physics Letters B, 387(3):642-650, 24 październik 1996. arXiv:hep-ph/9608346.
  • [129] Hegyi S.: H-function extension of the NBD in the light of experimental data. Physics Letters B, 414(1-2):210-219, listopad 1997. arXiv:hep-ph/9707322.
  • [130] Hegyi S.: H-function extension of the NBD: further applications. Physics Letters B, 417:186-192, 15 styczeń 1998. arXiv:hep-ph/9708241.
  • [131] Hegyi S.: A powerful generalization of the NBD suggested by Peter Carruthers. Proc. VIII Int. Workshop on Multiparticle Production, strony 272-286, Matrahaza (Hungary), 1999. World Scientific.
  • [132] Helstrom C. W.: Statystyczna teoria detekcji. WNT, Warszawa, 1964.
  • [133] Helstrom C. W., Ritcey J. A.: Evaluating radar detection probabilities by steepest descent integration. IEEE Transactions on Aerospace and Electronic Systems, 20(5):624-634, wrzesień 1984.
  • [134] Higham N. J.: Stable iterations for the matrix square root. Numerical Algorithms, 15(2):227-242, 1997.
  • [135] Hippenstiel R. D.: Detection Theory: Applications and Digital Signal Processing. CRC Press, Boca Raton, 2002.
  • [136] Horváth A., Telek M.: Approximating heavy tailed behavior with phase type distributions. Proc. of 3rd International Conference on Matrix-Analytic Methods in Stochastic Models, Advances in Matrix-Analytic Methods for Stochastic Models, strony 191-214, Leuven (Belgium), czerwiec 2000.
  • [137] Horváth A., Telek M.: PhFit: A general phase-type fitting tool. Proc. of 12th Performance TOOLS, tom 2324 serii Lecture Notes in Computer Science, strony 82-91, London (UK), kwiecień 2002. Imperial College.
  • [138] Howard R. A.: System analysis of semi-Markov processes. IEEE Transactions on Military Electronics, 8(2): 114-124, kwiecień 1964.
  • [139] Howard R. A.: Dynamic Probabilistic Systems, tom I: Markov Models. John Wiley & Sons, New York, 1971.
  • [140] Howard R. A.: Dynamic Probabilistic Systems, tom II: Semi-Markov and Decision Processes. John Wiley & Sons, New York, 1971.
  • [141] Huggins W. H.: Signal-flow graphs and random signals. Proceedings of the IRE, 45(1):74-86, styczeń 1957.
  • [142] Huzurbazar A. V.: Flowgraph models for generalized phase type distributions having non-exponential waiting times. Scand. J. Statist., 26(1):145-157, marzec 1999.
  • [143] Igence TWP web site, Technical Background : The calculation and modelling of radar performance. Session 8: Clutter modelling and analysis. http://www.igencetwp.com/technical/sessions/session8.pdf, 14 listopad 2003.
  • [144] Igence TWP web site, Technical Background : The calculation and modelling of radar performance. Session 9: Clutter simulation techniques. http://www.igencetwp.com/technical/sessions/session9.pdf, 14 listopad 2003.
  • [145] Ilow J., Hatzinakos D.: Applications of the empirical characteristic function to estimation and detection problems. Signal Processing, 65(2):199-219, marzec 1998.
  • [146] Ilow J., Leung H.: No evidence of stable distributions in radar clutter. Proc. The 6th IEEE Higher Order Statistics Workshop, strony 2487-2490, Banff (Canada), lipiec 1997.
  • [147] Jakeman E.: On the Statistics of K-distributed noise. J. Phys. A: Math. Gen., 13:31-48, 1980.
  • [148] Jakeman E., Pusey P. N.: A model for non-Rayleigh sea echo. IEEE Transactions on Antennas and Propagation, 24(6):806-814, listopad 1976.
  • [149] Jakubiak A.: Metody klasyfikacji radiolokacyjnych zakłóceń biernych, tom 126 serii Prace Naukowe Politechniki Warszawskiej. Elektronika. Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa, 2000.
  • [150] Jakubowski J., Sztencel R.: Wstęp do teorii prawdopodobieństwa. SCRIPT, Warszawa, wydanie III, 2004.
  • [151] Jao J. K.: Amplitude distribution of composite terrain radar clutter and the K-distribution. IEEE Transactions on Antennas and Propagation, 32(10): 1049-1062, październik 1984.
  • [152] Jarvis J. P, Shier D. R.: Graph-theoretic analysis of finite Markov chains. Shier D. R., Wallenius K. T., redaktorzy, Applied Mathematical Modeling: A Multidisciplinary Approach, rozdział 13. CRC Press, 1999.
  • [153] Jay E., Ovarlez J.-P, Declercq D., Duvaut R: BORD: bayesian optimum radar detector. Signal Processing, 83(6):1151-1162, czerwiec 2000.
  • [154] Jay E., Ovarlez J.-P, Declercq D., Duvaut P: Evaluation of radar detection performances in low grazing angle clutter environment. Low Grazing Angle Clutter: Its Characterization, Measurement and Application, strony 38-1-38-10. NATO Research and Technology Organization, październik 2000. Proc. of the RTO Sensors and Electronics Technology Panel (SET) Symposium, held in Laurel (MD, USA), 25-27 April 2000.
  • [155] Jay E., Ovarlez J.-P, Duvaut P: New methods of radar performance analysis. Signal Processing, 80(12):2527-2540, grudzień 2000.
  • [156] Johnson G. E.: Construction of particular random processes. Proceedings of the IEEE, 82(2):270-285, luty 1994.
  • [157] Johnson N. L., Kotz S., Balakrishnan N.: Continuous Univariate Distributions, tom 1. John Wiley & Sons, New York, wydanie drugie, 1994.
  • [158] Johnson W. R: The curious history of Faá di Bruno's formula. The American Mathematical Monthly, 109(3):217-234, marzec 2002.
  • [159] Канащенков А. И., Меркулов В.И., redaktorzy: Защита радиолокационных систем от помех: состояние и тенденции развития. Радиотехника, Москва, 2003.
  • [160] Karlin S., Studden W. J.: Tchebycheff systems: With applications in analysis and statistics, tom XV serii Pure and Applied Mathematics. Interscience Publishers John Wiley & Sons, New York, 1966.
  • [161] Kato F. H.: Discrete time portfolio analysis. Praca magisterska, University of Sao Paulo, 2004.
  • [162] Kelker D.: Distribution theory of spherical distributions and a location-scale parameter generalization. Sankhyā Ser. A, 32:419-438, 1970.
  • [163] Keyes T. K., Tucker W. T.: The K-distribution for modeling the envelope amplitude of a backscattered signal. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 46(4):883-887, lipiec 1999.
  • [164] Kilbas A. A., Bonilla B., Rivero M., Rodríguez J., Trujillo J.: Composition of Bessel type integral transform with fractional operators on spaces Fpµ and F'pµ. Fract. Calc. Appl. Anal., 1(2):135-150, 1998.
  • [165] Kilbas A. A., Koroleva A. A.: Integral transform with the extended generalized Mittag-Leffler function. Mathematical Modelling and Analysis, 11 (2): 161-174, 2006.
  • [166] Kilbas A. A., Saigo M.: On asymptotics of Fox's H-function at zero and infinity. Rusev P., redaktor, Transform Methods & Special Functions, Sofia'94. Proc. of the 1st International Workshop, strony 99-122, Bankya (Bułgaria), 12-17 sierpień 1994. SCT Publishing. Sofia, Bułgaria, 1995.
  • [167] Kilbas A. A., Saigo M.: On the H-function. J. Appl. Math. Stoch. Anal., 12(2): 191-204, 1999.
  • [168] Kilbas A. A., Saigo M., Saxena R. K., Trujillo J. J.: On the Krätzel function. Abstracts, International Congress MASSEE'2003, Borovetz (Bułgaria), 15-21 wrzesień 2003.
  • [169] Kingman J. F. C.: Procesy Poissona. PWN, Warszawa, 2002.
  • [170] Kiryakova V.: Generalized Fractional Calculus and Applications. Numer 301 serii Pitman Research Notes in Math. Longman Sci. & Technical, Harlow (UK), 1994. Wydanie wspólne z John Wiley and Sons, Inc., New York.
  • [171] Kiryakova V. S.: Multiple (multiindex) Mittag-Leffler functions and relations to generalized fractional calculus. J. Comput. Appl. Math., 118(1-2):241-259, 2000.
  • [172] Knuth D. E.: The Art of Computer Programming, tom II: Seminumerical Algorithms. Addison-Wesley, Reading, 1969.
  • [173] Kollar L: Statistical theory of quantization: Results and limits. Periodica Polytechnica Ser. Electrical Engineering, 28(2-3):173-189, 1984.
  • [174] Корн Г., Корн Т.: Справочник по математике для научных работников и инженеров. Определения, теоремы, формулы. Наука, Москва, 1984.
  • [175] Krasznovszky S.: Analysis of the KW distribution using a generalization of the Meijer's G-function. Mod. Phys. Lett. A, 8:483-490, 1993.
  • [176] Krätzel E.: Eine verallgemeinerung der Laplace- und Meijer-transformation. Wiss. Z. Univ. Jena Math. Naturw. Reihe, 5:369-381, 1965.
  • [177] Krätzel E.: Integral transformations of Bessel-type. Dimovski I., redaktor, Generalized Functions and Operational Calculus, strony 148-155, Varna (Bułgaria), 29 wrzesień - 6 październik 1975. Publishing House of the Bulgarian Academy of Sciences. Sofia, Bułgaria, 1979.
  • [178] Krätzel E., Menzel H.: Verallgemeinerte Hankel-funktionen. Publ. Math. Debrecen, 18(1-4):139-147, 1971.
  • [179] Kryachko E. S., Koga T.: On classical theory of moments: Finite-set-of-moments approach. I. Nonnegative distribution: Its even moments and Hankel transform. Journal of Mathematical Physics, 28(1):8-14, styczeń 1987.
  • [180] Kulpa K., Nałęcz M.: Odporne metody detekcji sygnału na tle zakłóceń morskich. Proceedings of the IV International Conference on Modern Radars, Zakopane, 1993.
  • [181] Kulpa K., Nałęcz M., Misiurewicz J.: Selected problems of 3-D target tracking. Proceedings of the XIII International Conference on Microwaves, Radar and Wireless Communications MIKON-2000, tom 2, strony 630-633, Wrocław (Poland), 22-24 maj 2000.
  • [182] Kulpa K., Wojtkiewicz A., Nałęcz M.: Wielofunkcyjny blok przetwarzania sygnałów cyfrowych radaru lotniczego kontroli strefy ekonomicznej. Materiały Krajowego Sympozjum Telekomunikacji, strony 125-132, Bydgoszcz, wrzesień 1995.
  • [183] Kulpa K., Wojtkiewicz A., Nałęcz M., Misiurewicz J.: The simple method for analysis of nonlinear frequency distortions in FMCW radar. Proceedings of the XIII International Conference on Microwaves, Radar and Wireless Communications MIKON-2000, tom 1, strony 235-238, Wrocław (Poland), 22-24 maj 2000.
  • [184] Kulpa K., Wojtkiewicz A., Nałęcz M., Misiurewicz J.: The simple analysis method of nonlinear frequency distortions in FMCW radar. Journal of Telecommunications and Information Technology, 2001(4):26-29, 2001.
  • [185] Kulshrestha P. K.: Asymptotic behavior of a class of integrals. Rendiconti di Matematica, Serie VI, 6(2):361-379, 1973.
  • [186] La Cour B. R.: Statistical characterization of active sonar reverberation using extreme value theory. IEEE Journal of Oceanic Engineering, 29(2):310-316, kwiecień 2004.
  • [187] Lakić S.: A one parameter method for the matrix inverse square root. Applications of Mathematics, 42(6):401-410, 1997.
  • [188] Lang A., Arthur J. L.: Parameter approximation for phase-type distributions. Chakravarty S. R., Alfa A. S., redaktorzy, Matrix-Analytic Methods in Stochastic Models, tom 183 serii Lecture Notes in Pure and Appl. Math., strony 151-206. Marcel Dekker, New York, 1997.
  • [189] Lawless J. F.: Inference in the generalized gamma and log gamma distributions. Technometrics, 22(3):409-419, sierpień 1980.
  • [190] Lebiediev N. N.: Funkcje specjalne i ich zastosowania. PWN, Warszawa, 1957.
  • [191] Leipnik R. B.: On lognormal random variables. I. The characteristic function. J. Austral. Math. Soc. Ser. B, 32(3):327-347, 1991.
  • [192] Lew H., Drumheller D. M.: Estimation of non-Rayleigh clutter and fluctuating-target models. IEE Proceedings Pt. F - Radar, Sonar and Navigation, 149(5):231-241, październik 2002.
  • [193] Liakhovetski G. V.: An algorithm for a series expansion of the Meijer G-function. Integral Transforms and Special Functions, 12(1):53-64, 2001.
  • [194] van de Liefvoort A.: Realization from both the Markov parameters and the moments. Proc. of the 32nd Midwest Symposium on Circuits and Systems, tom 1, strony 386-389, Champaign (IL, USA), 14-16 sierpień 1989.
  • [195] Lindsay B. G., Basak P.: Moments determine the tail of a distribution (but not much else). The American Statistician, 54(4):248-251, 2000.
  • [196] Lord R. D.: The use of the Hankel transform in statistics. I. General theory and examples. Biometrika, 41(1/2):44-55, czerwiec 1954.
  • [197] Lord R. D.: The use of the Hankel transform in statistics. II. Methods of computation. Biometrika, 41(3/4):344-350, grudzień 1954.
  • [198] Lukacs E.: Characteristic functions. Griffin, London, wydanie drugie, 1970.
  • [199] Luke Y. L.: The Special Functions and Their Approximations, Vol. I, tom 53 serii Mathematics in Science and Engineering. Academic Press Inc., New York, 1969.
  • [200] Luke Y. L.: Mathematical Functions and Their Approximations. Academic Press Inc., New York, 1975.
  • [201] Ma N.: Complete multinomial expansions. Applied Mathematics and Computation, 124(3):365-370, grudzień 2001.
  • [202] MacLeod A. J.: Algorithm 757: MISCFUN, a software package to compute uncommon special functions. ACM Trans. Math. Software, 22(3):288-301, wrzesień 1996.
  • [203] Mainardi F., Pagnini G., Saxena R. K.: Fox H functions in fractional diffusion. J. Comput. Appl. Math., 178(1-2):321-331, 2005.
  • [204] Manning W. G., Basu A., Mullahy J.: Generalized modeling approaches to risk adjustment of skewed outcomes data. Harris School Working Paper, Series 03.13, wrzesień 2003.
  • [205] Marcum J. I.: A statistical theory of target detection by pulsed radar. IRE Transactions on Information Theory, 6(2):59-267, kwiecień 1960. (with Mathematical Appendix).
  • [206] Marier L. J. Jr.: Correlated K-distributed clutter generation for radar detection and track. IEEE Transactions on Aerospace and Electronic Systems, 31(2):568-580, kwiecień 1995.
  • [207] Mason S. J.: Feedback theory - some properties of signal flow graphs. Proceedings of the IRE, 41(9): 1144-1156, wrzesień 1953.
  • [208] Mathai A.: An expansion of Meijer's G-function in the logarithmic case with applications. Math. Nachr., 48(1-6):129-139, 1970.
  • [209] Mathai A., Haubold H.: Review of mathematical techniques applicable in astrophysical reaction rate theory. Astrophysics and Space Science, 282(1):265-280, marzec 2002.
  • [210] Mathai A. M.: A Handbook of Generalized Special Functions for Statistical and Physical Sciences. Oxford University Press, New York, 1993.
  • [211] Mathai A. M., Saxena R. K.: The H-Function with Applications in Statistics and Other Disciplines. Wiley Eastern Ltd., New Delhi, 1978.
  • [212] McCullagh P: Does the moment-generating function characterize a distribution? The American Statistician, 48(3):208, sierpień 1994.
  • [213] Medhi J.: Stochastic models in gueueing theory. Academic Press (An imprint of Elsevier Science), Amsterdam, wydanie drugie, 2003.
  • [214] Mehta N. B., Goldsmith A. J.: Effects of mobility on PRMA. IEEE Transactions on Communications, 50(3):400-405, marzec 2002.
  • [215] Meini B.: The matrix square root from a new functional perspective: theoretical results and computational issues. SIAM J. Matrix Anal. Appl., 26(2):362-376, 2004/2005.
  • [216] Mejail M. E., Frery A. C., Jacobo-Berlles J., Bustos O. H.: Approximation of distributions for SAR images: proposal, evaluation and practical consequences. Latin American Applied Research, 31:83-92, 2001.
  • [217] Mejail M. E., Jacobo-Berlles J., Frery A. C., Bustos O. H.: Parametric roughness estimation in amplitude SAR images under the multiplicative model. Revista de Teledetección, 13:37-49, czerwiec 2000.
  • [218] Metzler R., Klafter J.: The random walk's guide to anomalous diffusion: a fractional dynamics approach. Physics Reports, 339:1-77, 2000.
  • [219] Middleton D.: Statistical-physical models of electromagnetic interference. IEEE Transactions on Electromagnetic Compatibility, 19(3):106-127, sierpień 1977.
  • [220] Middleton D.: New physical-statistical methods and models for clutter and reverberation: The KA-distribution and related probability structures. IEEE Journal of Oceanic Engineering, 24(3):261-284, lipiec 1999.
  • [221] Miller A. S., Moskowitz I. S.: Reduction of a class of Fox-Wright Psi functions for certain rational parameters. Computers & Mathematics with Applications, 30(11):73-82, 1995.
  • [222] von Mises R.: Mathematical theory of probability and statistics. Academic Press, New York, 1964. Edited and Complemented by Hilda Geiringer.
  • [223] Misiurewicz J., Nałęcz M., Kulpa K., Czekała Z.: Experiments with helicopter detection in a surveillance radar. Proceedings of the German Radar Symposium (GRS 2002), strony 145-149, Bonn (Germany), 3-5 wrzesień 2002.
  • [224] Misiurewicz J., Wojtkiewicz A., Nałęcz M., Kulpa K.: Unambiguous velocity estimation of fast objects in FMCW radars. Proceedings of the XXIInd National Conference on Circuit Theory and Electronic Devices, tom 1, strony 413-418, Warszawa - Stare Jabłonki (Poland), 20-23 październik 1999.
  • [225] Mitchell K., Place J., van de Liefvoort A.: Analytic modeling with matrix exponential distributions. Proc. CSEE'95, tom 27 serii SCS Simulation Series, Las Vegas (NE, USA), styczeń 1995.
  • [226] Mitchell K., Sohraby K., van de Liefvoort A., Place J.: Approximation models of wireless cellular networks using moment matching. IEEE Journal on Selected Areas in Communications, 19(11):2177-2190, listopad 2001.
  • [227] Moran B.: Mathematics of radar. Byrnes J. S., redaktor, Twentieth Century Harmonic Analysis - A Celebration, tom 33 serii NATO SCIENCE SERIES: II: Mathematics, Physics and Chemistry, strony 295-328. Kluwer Academic Publishers, Dordrecht, wrzesień 2001. Proceedings of the NATO Advanced Study Institute, held in Il Ciocco, Italy, 2-15 July 2000.
  • [228] Morgan C. J., Moyer L. R., Wilson R. S.: Optimal radar threshold determination in Weibull clutter and Gaussian noise. IEEE Aerospace and Electronic Systems Magazine, 11(3):41-43, marzec 1996.
  • [229] Morse P. M., Feshbach H.: Methods of Theoretical Physics. Part I: chapters 1 to 8. McGraw-Hill, New York, 1953.
  • [230] Moser G., Zerubia J., Serpico S. B.: Finite mixture models and stochastic expectation-maximization for SAR amplitude probability density function estimation based on a dictionary of parametric families. Proceedings 2004 IEEE International Geoscience and Remote Sensing Symposium, IGARSS'04, tom 2, strony 1510-1513, 20-24 wrzesień 2004.
  • [231] Nair V. C.: On the Laplace transform - I. Portugaliae Mathematica, 30(1):57-69, 1971.
  • [232] Nakagami M.: The m-distribution, a general formula of intensity of rapid fading. Hoffman W. C., redaktor, Statistical Methods in Radio Wave Propagation, strony 3-36, Oxford (England), 1960. Pergamon Press. Proceedings of a Symposium held at the University of California.
  • [233] Nałęcz M.: Forth compiler for Motorola DSP563xx. Proceedings of the International Conference on Signal Processing Applications and Technology ICSPAT'2000, Dallas (TX, USA), 16-19 październik 2000. CD-ROM.
  • [234] Nałęcz M.: Zastosowanie H-rozkładów i rozkładów macierzowo-wykładniczych do modelowania zakłóceń radiolokacyjnych. Materiały VI Seminarium - Radiokomunikacja i Techniki Multimedialne, strony 83-94, Warszawa (Poland), 7 grudzień 2005.
  • [235] Nałęcz M.: Graph-theoretic computation of characteristic function based on representation of phase-type distribution. Performance Evaluation, 64(6):591-611, lipiec 2007.
  • [236] Nałęcz M., Kulpa K.: Range and azimuth estimation using raw data in DSP-based radar system. Proceedings of the International Conference on Microwaves and Radar, MIKON, tom 3, strony 871-875, Kraków (Poland), 20-22 maj 1998.
  • [237] Nałęcz M., Kulpa K., Misiurewicz J., Wojtkiewicz A.: Signal processing using a network of digital signal processors in FMCW radar system. Proceedings of the International Radar Symposium IRS 98, tom II, strony 505-514, Monachium (Niemcy), 1998.
  • [238] Nałęcz M., Kulpa K., Piątek A., Wojdołowicz G.: Przetwarzanie sygnałów za pomocą sieci procesorów sygnałowych. Materiały Krajowego Sympozjum Telekomunikacji, Bydgoszcz, 10-12 wrzesień 1997.
  • [239] Nałęcz M., Kulpa K., Piątek A., Wojdołowicz G.: Scalable hardware and software architecture for radar signal processing systems. Proceedings of the RADAR 97 Conference, Edinburgh (UK), 14-16 październik 1997.
  • [240] Nałęcz M., Kulpa K., Rytel-Andrianik R., Plata S., Dawidowicz B.: Data recording and processing in FMCW SAR system. Proceedings of the International Radar Symposium (IRS 2004), strony 171-175, Warszawa (Poland), 19-21 maj 2004.
  • [241] Nałęcz M., Kulpa K., Śliwa E.: Uproszczona metoda wyznaczania parametrów dwuetapowego algorytmu detekcji sekwencyjnej. Materiały Krajowego Sympozjum Telekomunikacji, strony 90-99, Bydgoszcz, wrzesień 1995.
  • [242] Nałęcz M., Mordzonek M., Kulpa K., Piątek A.: Hardware/software co-design in DSP-based radar and sonar systems. Proceedings of the International Radar Symposium (IRS 2004), strony 143-148, Warszawa (Poland), 19-21 maj 2004.
  • [243] Nałęcz M., Piątek A.: DREAMS: DSP real-time multiprocessor system. Proceedings of The International Conference on Signal Processing Applications and Technology ICSPAT'1997, strony 884-888, San Diego (CA, USA), 14-17 wrzesień 1997.
  • [244] Nałęcz M., Piątek A.: A system approach to DSP-based software radar. Proceedings of the German Radar Symposium (GRS 2002), strony 595-599, Bonn (Germany), 3-5 wrzesień 2002.
  • [245] Nałęcz M., Rytel-Andrianik R., Wojtkiewicz A.: DSP realization of optimal signal processing algorithms in FMCW radar. Proceedings of the German Radar Symposium (GRS 2002), strony 437-441, Bonn (Germany), 3-5 wrzesień 2002.
  • [246] Nałęcz M., Rytel-Andrianik R., Wojtkiewicz A.: Micro-doppler analysis of signal received by FMCW radar. Proceedings of the International Radar Symposium (IRS 2003), strony 651-656, Dresden (Germany), 30 wrzesień - 2 październik 2003.
  • [247] Nałęcz M., Śliwa E., Kulpa K.: Algorithms for radar signal processing in DBS systems. Proc. of the XV-th National Conference "Circuit Theory and Electronic Circuits", tom 2, strony 418-424, Szczyrk, 20-23 październik 1992.
  • [248] Nałęcz M., Wojtkiewicz A., Kulpa K., Klembowski W., Miłosz J.: Application of polynomial phase modeling for estimation of signal parameters in FMCW radar. Proceedings of the International Radar Conference India (IRSI-2001), strony 795-803, Bangalore (India), 11-14 grudzień 2001.
  • [249] Nathanson F. E., Reilly J. P., Cohen M. N.: Radar Design Principles: Signal Processing and the Environment. Seitech, Mendham (NJ, USA), wydanie drugie, 1999. A reprint of the 1991 edition by McGraw-Hill, Inc.
  • [250] Neumann K.: Recent advances in temporal analysis of GERT networks. Zeitschrift für Operations Research, 23(5): 153-177, 1979.
  • [251] Neuts M. F.: Matrix-geometric solutions in stochastic models, rozdział 2. Probability Distributions of Phase Type, strony 41-80. Johns Hopkins series in the mathematical sciences. Johns Hopkins, Baltimore (MD, USA), 1981.
  • [252] Noga J. L.: Bayesian State-Space Modelling of Spatio-Temporal Non-Gaussian Radar Returns. Praca doktorska, University of Cambridge, grudzień 1998.
  • [253] Norland R.: Sea clutter behaviour as a function of range resolution and frequency. Low Grazing Angle Clutter: Its Characterization, Measurement and Application, strony 5-1-5-6, październik 2000.
  • [254] O'Cinneide C. A.: Characterization of phase-type distributions. Comm. Statist. Stochastic Models, 6(1): 1-57, 1990.
  • [255] O'Cinneide C. A.: Phase-type distributions: open problems and a few properties. Comm. Statist. Stochastic Models, 15(4):731-757, 1999.
  • [256] Olsson M.: Estimation of phase-type distributions from censored data. Scand. J. Statist., 23(4):443-460, 1996.
  • [257] Olver F. W. J.: Asymptotics and Special Functions. Computer Science and Applied Mathematics. Academic Press, New York, 1974.
  • [258] Oppenheim A. V., Frisk G. V., Martinez D. R.: An algorithm for the numerical evaluation of the Hankel transform. Proceedings of the IEEE, 66(2):264-265, luty 1978.
  • [259] Osiowski J.: Zarys rachunku operatorowego. Teoria i zastosowania w elektrotechnice. WNT, Warszawa, wydanie drugie zmienione, 1972.
  • [260] Osiowski J., Szabatin J.: Podstawy teorii obwodów, tom III. WNT, Warszawa, 1995.
  • [261] Osogami T., Harchol-Balter M.: Necessary and sufficient conditions for representing general distributions by Coxians. Technical Report CMU-CS-02-178, School of Computer Science, Carnegie Mellon University, Pittsburgh (PA, USA), wrzesień 2002.
  • [262] Osogami T., Harchol-Balter M.: A closed-form solution for mapping general distributions to minimal PH distributions. Technical Report CMU-CS-03-114, School of Computer Science, Carnegie Mellon University, Pittsburgh (PA, USA), luty 2003.
  • [263] Osogami T., Harchol-Balter M.: Necessary and sufficient conditions for representing general distributions by Coxians. Proceedings of the 13th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation (TOOLS 2003), strony 182-199, Urbana (IL, USA), 2-5 wrzesień 2003.
  • [264] Osogami T., Harchol-Balter M.: A closed-form solution for mapping general distributions to minimal PH distributions. Proceedings of the 13th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation (TOOLS 2003), strony 200-217, Urbana (IL, USA), 2-5 wrzesień 2003.
  • [265] Pacut A.: Prawdopodobieństwo. Teoria. Modelowanie probabilistyczne w technice. WNT, Warszawa, 1985.
  • [266] Papoulis A.: Prawdopodobieństwo, zmienne losowe i procesy stochastyczne. WNT, Warszawa, 1972.
  • [267] Paris R. B., Kaminski D.: Asymptotics and Mellin-Barnes Integrals. Numer 85 serii Encyclopedia of Mathematics and its Applications. Cambridge University Press, Cambridge, 2001.
  • [268] Petkovšek M.: Hypergeometric solutions of linear recurrences with polynomial coefficients. J. Symbolic Comput., 14(2-3):243-264, sierpień - wrzesień 1992.
  • [269] Petkovšek M., Salvy B.: Finding all hypergeometric solutions of linear differential equations. Research Report RR-1907, INRIA, 1994. (Apr. 1993).
  • [270] Pickands J. III: Statistical inference using extreme order statistics. The Annals of Statistics, 3(1):119-131, 1975.
  • [271] Piessens R.: The Hankel transform. Poularikas A. D., redaktor, The Transforms and Applications Handbook: Second Edition, rozdział 9. CRC Press, Boca Raton, 2000.
  • [272] Piotrkowski M.: Distribution independent CFAR detector using extreme value theory. Proceedings of the International Radar Symposium IRS 2006, strony 75-80, Kraków (Poland), 24-26 maj 2006.
  • [273] Piotrkowski M., Nałęcz M., Świdzińska B.: Radar target detection and classification using fractal dimension analysis. Proceedings of the International Radar Symposium (IRS 2003), strony 657-662, Dresden (Germany), 30 wrzesień - 2 październik 2003.
  • [274] Piotrkowski M., Nałęcz M., Świdzińska B.: Influence of SNR on the estimated fractal dimension of radar signal. Proceedings of the International Radar Symposium (IRS 2004), strony 239-244, Warszawa (Poland), 19-21 maj 2004.
  • [275] Plucińska A., Pluciński E.: Elementy probabilistyki. PWN, Warszawa, 1979.
  • [276] Posner F. L.: Spiky sea clutter at high range resolutions and very low grazing angles. IEEE Transactions on Aerospace and Electronic Systems, 38(1):58-73, styczeń 2002.
  • [277] Postnikov E. B.: About calculation of the Hankel transform using preliminary wavelet transform. Journal of Applied Mathematics, 2003(6):319-325, 2003.
  • [278] Primak S. L., Lyandres V. Z.: On the generation of the baseband and narrowband non-Gaussian processes. IEEE Transactions on Signal Processing, 46(5):1229-1237, maj 1998.
  • [279] Pritsker A. A. B., Happ W. W.: GERT: Graphical Evaluation and Review Technique. Part I. Fundamentals. The Journal of Industrial Engineering, XVII(5):267-274, maj 1966.
  • [280] Pritsker A. A. B., Whitehouse G. E.: GERT: Graphical Evaluation and Review Technique. Part II. Probabilistic and industrial engineering applications. The Journal of Industrial Engineering, XVII(6):293-301, czerwiec 1966.
  • [281] Прудников А. П., Брычков Ю. А., Маричев О. И.: Интегралы и рыады, tom 2: Специальные функции. Наука, Москва, 1983.
  • [282] Прудников А. П., Брычков Ю. А., Маричев О. И.: Интегралы и ряды, tom 1: Элементарные функции. Физико-Математическая Литература, Москва, 2003. 2-e изд. исправ.
  • [283] Прудников А. П., Брычков Ю. А., Маричев О. И.: Интегралы и ряды, tom 2: Специальные функции. Физико-Математическая Литература, Москва, 2003. 2-e изд. исправ.
  • [284] Прудников А. П., Брычков Ю. А., Маричев О. И.: Интегралы и ряды, tom 3: Специальные функции. Ополнительныеглавы. Физико-Математическая Литература, Москва, 2003. 2-e изд. исправ.
  • [285] Pyke R.: Markov renewal processes with finitely many states. Ann. Math. Stat., 32:1243-259, 1961.
  • [286] Rabiner L. R., Gold B.: Theory and Application of Digital Signal Processing. Prentice-Hall, Englewood Cliffs, 1975.
  • [287] Ralston A.: Wstęp do analizy numerycznej. PWN, Warszawa, wydanie III, 1983.
  • [288] Rangaswamy M., Weiner D., Öztürk A.: Non-Gaussian random vector identification using spherically invariant random processes. IEEE Transactions on Aerospace and Electronic Systems, 29(1):111-124, styczeń 1993.
  • [289] Reiss R.-D., Thomas M.: Statistical analysis of extreme values. Birkhauser Verlag, Basel, wydanie second, 2001. From insurance, finance, hydrology and other fields, With 1 CD-ROM (Windows).
  • [290] Rinehart R. R: The equivalence of definitions of a matric function. The American Mathematical Monthly, 62:395-414, 1955.
  • [291] Riska A., Diev V., Smirni E.: An EM-based technique for approximating long-tailed data sets with PH distributions. Performance Evaluation, 55(1-2):147-164, styczeń 2004.
  • [292] Ritcey J. A., Hines J. L.: Performance of MAX family of order-statistic CFAR detectors. IEEE Transactions on Aerospace and Electronic Systems, 27(1):48-57, styczeń 1991.
  • [293] Рыжик И. М., Градштейн И. С.: Таблицы интегралов, сумм, pядов и произведений. Государств. Издат. Течн.-Теор. Лит., Мoсква, 1951. Издание третье, преработанное.
  • [294] Salvy B.: Finding all hypergeometric solutions of linear differential equations. Salvy B., redaktor, Algorithms seminar, 1996-1997, numer RR-3267 serii Research Report, strony 45-50. INRIA, wrzesień 1997.
  • [295] Sangston K. J., Gini F., Greco M. V., Farina A.: Structures for radar detection in compound Gaussian clutter. IEEE Transactions on Aerospace and Electronic Systems, 35(2):445-458, kwiecień 1999.
  • [296] Saxena R. K., Mathai A. M., Haubold H. J.: Astrophysical thermonuclear functions for Boltzmann-Gibbs statistics and Tsallis statistics. Physica A: Statistical Mechanics and its Applications, 344(3-4):649-656, 15 grudzień 2004.
  • [297] Sayama S., Sekine M.: Weibull distribution and K-distribution of sea clutter observed by X-band radar and analyzed by AIC. IEICE Transactions on Communications, E83-B(9):1978-1982, wrzesień 2000.
  • [298] Schleher D. C.: MTI and Pulsed Doppler Radar. Artech House, Boston (MA, USA), 1991.
  • [299] Shi D., Guo J., Liu L.: SPH-distributions and the rectangle-iterative algorithm. Chakravarty S. R., Alfa A. S., redaktorzy, Matrix-Analytic Methods in Stochastic Models, tom 183 serii Lecture Notes in Pure and Appl. Math., strony 207-224. Marcel Dekker, New York, 1997.
  • [300] Sidje R. B.: EXPOKIT: Software package for computing matrix exponentials. ACM Transactions on Mathematical Software, 24(1):130-156, marzec 1998.
  • [301] Sittler R. W.: Systems analysis of discrete Markov processes. IRE Transactions on Circuit Theory, 3(4):257-266, grudzień 1956.
  • [302] Skolnik M. I., redaktor: Radar handbook. McGraw-Hill, Boston (MA, USA), wydanie drugie, 1990.
  • [303] Snowden A.: Collection of mathematical articles. Dostępne pod adresem http://www.math.umd.edu/~asnowden/math-cont/dorfman.pdf, maj 2003. Przedstawione do nagrody "The 2003 J.R. Dorfman Prize for Undergraduate Research".
  • [304] Сосулин Ю. Г.: Теоpетические основы радиолокации и радионавигации. Радио и связь, Москва, 1992.
  • [305] Сосулин Ю. Г., Гаврилов К. Ю., Войткевич A., Наленч М.: Метод анализа и оптимизации многоканальных двухэтапных последователных обнаружителей. Журнал Росийской Академии Наук, Радиотдехника и Електроника, 41 (5):563-574, май 1996. English translation: Yu. G. Sosulin, K. Yu. Gavrilov, A. Wojtkiewich, M. Nalecz: A Method for the Analysis and Optimization of Multichannel Two-Stage Sequential Detectors, Journal of Communications Technology and Electronics, vol. 41, no. 6, pp. 520-530, May, 1996.
  • [306] Сосулин Ю. Г., Гаврилов К. Ю., Войткевич A., Наленч М.: Вопросы k-етапного обнаружения радиолокационных сигналов. Материалы Всеросийской научной конференции "Цифровая обработка мнногомерных сигналов" strony 14-26, Йошкар-Ола, Декабрь1996.
  • [307] Sosulin Yu. G., Gavrilov K. Yu., Wojtkiewicz A., Nałęcz M.: k-stage radar detection. Proceedings of the CIE International Conference of Radar, strony 100-105, Beijing (China), 8-10 październik 1996.
  • [308] Sosulin Yu. G., Gavrilov K. Yu., Wojtkiewicz A., Nałęcz M.: Multichannel two-stage detection of signals. IEEE Transactions on Aerospace and Electronic Systems, 36(3):793-809, lipiec 2000.
  • [309] Stacy E. W.: A generalization of the gamma distribution. Ann. Math. Statist., 33:1187-1192, 1962.
  • [310] Sullivan R. J.: Radar Foundations for Imaging and Advanced Concepts. Scitech, Raleigh (NC, USA), 2004.
  • [311] Swerling R: Probability of detection for fluctuating targets. IRE Transactions on Information Theory, 6(2):269-308, kwiecień 1960.
  • [312] Tan C. C., Beaulieu N. C.: On first-order Markov modeling for the Rayleigh fading channel. IEEE Transactions on Communications, 48(12):2032-2040, grudzień 2000.
  • [313] Taneda M. A., Takada J., Araki K.: The problem of the fading model selection. IEICE Transactions on Communications, E84-B(3):660-666, marzec 2001.
  • [314] Tang C., Yeung R. W.: A graph-theoretic approach to queueing analysis. Part I: Theory. Comm. Statist. Stochastic Models, 15(5):791-824, 1999.
  • [315] Teich M. C., Diament R: Multiply Stochastic representations for K distributions and their Poisson transforms. J. Opt, Soc. Am. A, 6(1):80-91, styczeń 1989.
  • [316] Telek M., Heindl A.: Matching moments for acyclic discrete and continuous phase-type distributions of second order. International Journal of Simulation, 3(3-4):47-57, 2003.
  • [317] Torriani H. H.: Constructive inverse function theorems. Letters in Mathematical Physics, 13(4):273-281, maj 1987.
  • [318] Turin W., van Nobelen R.: Hidden Markov modeling of flat fading channels. IEEE Journal on Selected Areas in Communications, 16(9):1809-1817, grudzień 1998.
  • [319] Walck C.: Hand-book on statistical distributions for experimentalists. Internal Note SUF-PFY/96-01, Particle Physics Group, Fysikum, Stockholm University, 11 grudzień 1996.
  • [320] Ward K. D., Baker C. J., Watts S.: Maritime surveillance radar. I. Radar scattering from the ocean surface. IEE Proceedings Pt. F - Radar and Signal Processing, 137(2):51-62, kwiecień 1990.
  • [321] Watts S., Baker C. J., Ward K. D.: Maritime surveillance radar. II: Detection performance prediction in sea clutter. IEE Proceedings Pt. F - Radar and Signal Processing, 137(2):63-72, kwiecień 1990.
  • [322] Whittaker E. T.: On the reversion of series. Gazeta de Matemática, XII(50):1, grudzień 1951.
  • [323] Widrow B., Kollár L, Liu M.-C.: Statistical theory of quantization. IEEE Transactions on Instrumentation and Measurement, 45(2):353-361, kwiecień 1996.
  • [324] Wieczorkowski R., Zieliński R.: Komputerowe generatory liczb losowych. WNT, Warszawa, 1997.
  • [325] Wieder T.: Algorithm 794: Numerical Hankel transform by the Fortran program HANKEL. ACM Transactions on Mathematical Software, 25(2):240-250, czerwiec 1999.
  • [326] Winston W. L.: Introduction to Probability Models - Operational Research, tom II, rozdział 5. Markov Chains, strony 180-217. Brooks/Cole, wydanie czwarte, 2004.
  • [327] Wojtkiewicz A., Jędrzejewski K., Misiurewicz J., Nałęcz M., Kulpa K.: Zastosowanie dwuwymiarowej analizy widmowej do wyznaczania położenia i prędkości obiektów wykrywanych przez radar FMCW. Materiały Krajowego Sympozjum Telekomunikacji, Bydgoszcz, 1997.
  • [328] Wojtkiewicz A., Kulpa K., Misiurewicz J., Nałęcz M.: Analysis of helicopter echo in FMCW radar. Proceedings of the XXIInd National Conference on Circuit Theory and Electronic Devices, tom 1, strony 407-412, Warszawa - Stare Jabłonki (Poland), 20-23 październik 1999.
  • [329] Wojtkiewicz A., Kulpa K., Nałęcz M.: A new analysis method for nonlinear modulation distortion in LFMCW radar. Proceedings of the International Conference on Signals and Electronic Systems ICSES'2000, strony 69-74, Ustroń (Poland), 17-20 październik 2000.
  • [330] Wojtkiewicz A., Misiurewicz J., Nałęcz M., Jędrzejewski K., Kulpa K.: Two-dimensional signal processing in FMCW radars. Materiały KKTOiUE, Koszalin (Poland), 1997.
  • [331] Wojtkiewicz A., Misiurewicz J., Nałęcz M., Jędrzejewski K., Kulpa K.: Metody estymacji prędkości obiektów wykrywanych przez radar FMCW. Materiały Krajowego Sympozjum Telekomunikacji, strony 401-407, Bydgoszcz, 8-10 wrzesień 1999.
  • [332] Wojtkiewicz A., Nałęcz M., Kulpa K.: A novel approach to signal processing in FMCW radar. Proceedings of the International Conference on Signals and Electronic Systems ICSES'2000, strony 63-68, Ustroń (Poland), 17-20 październik 2000.
  • [333] Wojtkiewicz A., Nałęcz M., Kulpa K., Klembowski W.: Use of polynomial phase modeling to FMCW radar, part C: Estimation of target acceleration in FMCW radars. Proceedings of the NATO Research and Technology Agency, Sensors & Electronics Technology Symposium on Passive and LPI (Low Probability Of Intercept) Radio Frequency Sensors, Warszawa (Poland), 23-25 kwiecień 2001. CD-ROM, paper #40C.
  • [334] Wojtkiewicz A., Nałęcz M., Kulpa K., Misiurewicz J.: DSP-based two-dimensional spectrum analyzer for FMCW radar. Materiały KKTOiUE, strony 511-516, Poznań - Kiekrz (Poland), 1998.
  • [335] Wojtkiewicz A., Nałęcz M., Kulpa K., Rytel-Andrianik R.: A novel approach to signal processing in FMCW radar. Bulletin of the Polish Academy of Sciences (Technical Sciences), 50(4):347-359, grudzień 2002.
  • [336] The Wolfram functions site. http://functions.wolfram.com
  • [337] Wong R., Zhao Y.-Q.: Smoothing of Stokes's discontinuity for the generalized Bessel function. Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci., 455(1984):1381-1400, 1999.
  • [338] Wright E. M.: The asymptotic expansion of the generalized Bessel function. Proc. London Math. Soc. (2), 38:257-270, 1935.
  • [339] Wright E. M.: The asymptotic expansion of the generalized hypergeometric function. J. London Math. Soc. (2), 10:286-293, 1935.
  • [340] Wright E. M.: The generalized Bessel function of order greater than one. Quart. J. Math., Oxford Ser., 11:36-48, 1940.
  • [341] Xhafa A., Tonguz O. K.: Dynamic priority queuing of handover calls in wireless networks: An analytical framework. IEEE Journal on Selected Areas in Communications, 22(5):904-916, czerwiec 2004.
  • [342] Yacoub M. D., Fraidenraich G., Santos Filho J. C. S.: Nakagami-m phase-envelope joint distribution. Electronics Letters, 41(5):259-261, marzec 3rd 2005.
  • [343] Янке Е., Эмде Ф., Леш Ф.: Специальные функции: Формулы, графики, таблицы. Hayкa, Mocквa, 1977. Издание третье, стереотипное
  • [344] Yao K.: A representation theorem and its applications to spherically-invariant random processes. IEEE Transactions on Information Theory, 19(5):600-608, wrzesień 1973.
  • [345] Yao K.: Spherically invariant random processes: Theory and applications. Bhargava V. K., Poor H. V., Tarokh V., Seokho Y., redaktorzy, Communications, Information and Network Security, tom 712 serii The International Series In Engineering and Computer Science, rozdział 16, strony 315-331. Kluwer Academic, Dordrecht, 2003.
  • [346] Yao K., Gao J.: Two statistical methods for modeling wireless fading and radar sea clutter phenomena. Proc. Sixth IMA International Conference on Mathematics in Signal Processing, strony 219-222, Cirecenster (England), 14-16 grudzień 2004.
  • [347] Yao K., Simon M. K., Biglieri E.: A unified theory on wireless communication fading statistics based on SIRP. Proc. Fifth IEEE Workshop on Signal Processing Advances in Wireless Communications, Lisboa (Portugal), 11-14 lipiec 2004.
  • [348] Yao R.: A proof of the steepest increase conjecture of a phase-type density. Stochastic Models, 18(1): 1-6, 2002.
  • [349] Zhai H., Kwon Y, Fang Y: Performance analysis of IEEE 802.11 MAC protocols in wireless LANs. Wirel. Commun. Mob. Comput., 4(8):917-931, grudzień 2004.
  • [350] Zhou M. C., Wang C.-H., Zhao X.: Automating Mason's rule and its application to analysis of stochastic Petri nets. IEEE Transactions on Control Systems Technology, 3(2):238-244, czerwiec 1995.
  • [351] Zoghbi A., Stojmenović L: Fast algorithms for generating integer partitions. Intern. J. Computer Math., 70(2):319-332, 1998.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA8-0024-0003
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.