Fuzzy Extreme Analysis in Time- and Frequency Domains

• Autorzy: Pogribny W. , Drzycimski M. , Drzycimski Z.
• Języki publikacji: EN

Abstrakty

EN

Very often, we are interested in the shape of a signal or an envelope of the signal or its spectrum. Classical extreme analysis (CEA) produces too many minor details of a signal shape. This fact, in the context of telecommunications, does not allow us to ensure a significant coefficient of a signal compression. Another option for signal analysis, based on the Delta Modulation (DM), lacks sufficient dynamic range at a relatively low sampling rate. One more "true envelope" manner is based on the cepstral analysis, and requires too many operations. Other methods are used for the definition of a signal envelope. The discrete Hilbert transform (DHT) is only expedient to capture an envelope of a narrowband signal and, moreover, requires too many mathematical operations. Other manners based on decimation, as well as the use of a signal rectifying followed by low-pass filtering do not always ensure sufficient accuracy and signal compression coefficient. Fuzzy EA (FEA) is free from similar drawbacks. Its first and second differences are compared with no zero limits, and that allows us to take into consideration only major details of the signal or spectrum shape. Consequently we obtain both an envelope of wideband signal, and a signal significant compression in real time. This article focuses on FEA features connected with the aforementioned tasks. Apart from the FEA algorithm, the article outlines some methods of signal reconstruction after FEA in both domains, and the structure of the FEA specializedprocessor. FEA application in both domains is demonstrated through examples.

Słowa kluczowe

EN

extreme analysis; envelope extraction; signal compression

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2011
• Tom: Vol. 57, No. 4
• Strony: 511--518
• Opis fizyczny: Bibliogr. 14 poz., wykr.

Twórcy

autor

Pogribny W.

autor

Drzycimski M.

autor

Drzycimski Z.

• University of Technology and Life Sciences, 7 Kaliskiego Ave., Bydgoszcz 85–796, Poland,

Bibliografia

• [1] G. Korn and T. Korn, Mathematical Handbook. New York: McGraw Hill, 1968.
• [2] J. Cacko, M. Bily, and J.Bukoveczky, Random Processes: Measurement, Analysis and Simulation. New York: Elsevier Science Publishing Company, 1988.
• [3] A. Rosenfeld and E. Johnston, “Angel Detection on Digital Curves,” IEEE Transactions on Computers, vol. C-22, pp. 875–878, 1973.
• [4] C. H. Teh and R. T. Chin, “On the Detection of Dominant Points on Digital Curves,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no. 8, pp. 859–872, 1989.
• [5] V. O. Pohribnyi (W. Pogribny), Z. Drzycimski, and I. Zielinski, “Compression of Images with Use of Differential Methods and Extreme Analysis,” in Mathematics of Data/Image Coding, Compression, and Encryption, M. S. Schmalz, Ed., 1998, pp. 176–184, Proceedings of SPIE, vol. 3456.
• [6] A. D. Poularikas, The Transforms and Applications Handbook, 2nd ed. Boca Raton FL: CRC Press LLC, 2000.
• [7] A. V. Oppenheim and R. Schafer, Discrete-time Signal Processing, 2nd ed. Upper Saddle River NJ: Prentice-Hall, Inc., 1998.
• [8] R. G. Lyons, Understanding Digital Signal Processing. New York: Addison Wesley Longman, 1997.
• [9] B. Boulet and L. Chartrand, Fundamentals of Signals and Systems. Boston: Da Vinci Engineering Press„ 2005.
• [10] A. Robel, F. Villavincenio, and X. Rodet, “On Cepstral and All-pole Based Spectral Envelop Modeling With Unknown Model Order,” Pattern Recognition Letters, vol. 28, no. 11, pp. 1343–1350, 2007.
• [11] W. Pogribny, Z. Drzycimski, and J. Zalewski, “Adaptacyjny sposób odtwarzania sygnałów,” 2003, patent UP RP No. 186190, IntCl H03M 7/00.
• [12] W. Pogribny, Z. Drzycimski, and J. Zalewski, “Adaptacyjny sposób odtwarzania sygnałów,” 2003, patent UP RP No. 186192, IntCl H03M 7/00.
• [13] W. Pogribny, Z. Drzycimski, and M. Drzycimski, “Fuzzy Extreme Analysis of Random Signals,” in Proceedings of the 6th International Conference QRM, Oxford, 2007, pp. 151–156.
• [14] W. Pogribny and M. Drzycimski, “Fuzzy Extreme Analysis for Signal Compression,” in ICSES 2008 Conference Proceedings, Kraków, 2008, pp. 31–34