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A Framework for Interval Quantization and Application to Interval Based Algorithms in Digital Signal Processing

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Języki publikacji
EN
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EN
In this article, we use the interval mathematics and targeted rounding by specific functions to establish a framework for interval quantization. The function approximation FId, that maps x to an interval [x1, x2] such that x1 is the largest floating point number less than or equal to x and x2 is the smallest floating point number greater than or equal to x, is used to establish the sampling interval and the levels of interval quantization. We show that the interval quantization levels (Nj) represent the specific quantization levels (nj ), that are comparable, according to Kulisch- Miranker order and are disjoint two by two. If an interval signal X[n] intercepts a quantization interval level Nj , then the quantized signal will be Xq[n] = Nj. Moreover, for the interval quantization error (E[n] = Xq[n] - X[n]) an estimate is shown due to the quantization step and the number of levels. It is also presented the definition of interval coding, in which the number of required bits depends on the amount of quantization levels. Finally, in an example can be seen that the the interval quantization level represent the classical quantization levels and the interval error represents the classical quantization error.
Wydawca
Rocznik
Strony
337--363
Opis fizyczny
Bibliogr. 15 poz., tab.
Twórcy
Bibliografia
  • [1] G. Alefeld and J. Herzberger, Introduction to Interval Computations, Academic Press, New York, 1983.
  • [2] M. A. Campos, G. P. Dimuro, A. C. R. Costa, J. F. F. Ara´ujo and A.M. Dias, Probabilidade Intervalar e Cadeias deMarkov Intervalar noMaple, Tendências emMatemática Aplicada e Computacional, No. 2, 3(2002), 53-62.
  • [3] M. M. C. Cruz, R. H. N. Santiago and A. D. D´oria Neto, Mathematical morphology for two valued gray-scale images with unde ned information, In: 8th International Symposium on Mathematical Morphology, 2008, Rio de Janeiro, Proceedings of the 8th International Symposium on Mathematical Morphology, 1(2008), 01-06.
  • [4] W. Edmonson, W. H. Lee and J. M. M. Anderson, Interval methods for sinusoidal parameter estimation: A comparative analysis, Reliable Computing, No. 3, 6(2000), 321-336.
  • [5] W. Edmonson, R. Gupte, S. Ocloo, J. Gianchandani and W. Alexander, Interval Arithmetic Logic Unit for Signal Processing and Control Applications, In: Proceedings of the NSF Workshop on Reliable Engineering Computing: Modeling Errors and Uncertainty in Engineering Computations, R.L. Muhanna and R.L. Mullen (eds.), Savannah, Georgia, 2006, 189-196.
  • [6] W. Edmonson, S. Ocloo, C. Williams and W. Alexander, The use of interval methods in signal processing and control for systems biology, In: Proceedings of the 2007 IEEE Symposium on Foudations of Computational Inteligence (FOCI2007) pp. 136-142.
  • [7] U. Kulisch andW. Miranker, Computer Arithmetic in Theory and Practice, New York: Academic Press, 1981.
  • [8] A. D. S. Lordelo, E. A. Juzzo and P. A. V. Ferreira, On the design of robust controllers using the interval diophantine equation, In: Proceedings of the IEEE International Symposium on Computer Aided Control System Design, Taipei, Taiwan, 2004, 173-178.
  • [9] A. Lyra, B. R. C. Bedregal, R. C. Bedregal and A. D. D´oria Neto, The Interval Digital Images, In: Processing, WSEAS Transactions on Circuits, Grécia, No. 2, 3(2004), 234-240.
  • [10] R. E. Moore,Methods and Applications of Interval Analysis, Society for Industrial and AppliedMathematics (SIAM), Philadelphia, 1979.
  • [11] R. E. Moore, Interval Analysis, Prentice Hall, New Jersey, 1966.
  • [12] M. L. Overton, Numerical Computing with IEEE Floating Point Arithmetic, SIAM, Philadelphia, 2001.
  • [13] J. G. Proakis and D. G. Manolakis, Digital Signal Processing, Principles, Algorithms and Applications, 3nd edition, Prentice Hall Internetional, INC, 1996.
  • [14] R. H. N. Santiago, B. R. C. Bedregal and B. M. Aci´oly, Formal Aspects of Correctness and Optimality of Interval Computations, Formal Aspects of Computing, No. 2, 18(2006), 231-243.
  • [15] R. M. P. Trindade, B. R. C. Bedregal and A. D. D´oria Neto, Basics Concepts of Interval Digital Signal Processing, In: World Congress on Science, Engineering and Technology, Paris, Proceedings of WCSET, 1(2008), 66-70.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0022-0062
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