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Quadratic Time-Frequency Analysis of Linear Time-Varying Systems

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Part of the book series: Applied and Numerical Harmonic Analysis ((ANHA))

Abstract

Viewed from a time-frequency (TF) perspective, the action of a linear time-varying (LTV) system consists of TF weightings and TF displacements. In this chapter, we study TF weighting and displacement effects using known and novel quadratic TF representations of LTV systems. In particular, we define and study two novel TF representations termed “input Wigner distribution” (IWD) and “output Wigner distribution” (OWD). The interpretations, various expressions, and fundamental properties of the IWD and OWD are discussed. In the case of a normal system, the IWD and OWD coincide and reduce to a single TF representation, the “Wigner distribution (WD) of an LTV system.”

In addition to the IWD and OWD, we define displacement spread quantities that globally characterize TF displacement effects. It is shown that positive semidefinite systems feature minimum TF displacements. The IWD and OWD of an “under spread” system (i.e., a system whose TF displacements are small) are shown to be approximately equal to each other and also to the squared Weyl symbol, to be approximately nonnegative, and to satisfy an approximate composition property. The application of the IWD and OWD to random LTV systems is briefly considered. Finally, we describe a WD-based TF design method for (normal) LTV systems with prescribed TF weightings and minimum TF displacements.

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References

  1. A. W. Naylor and G. R. Sell.Linear Operator Theory in Engineering and Science2nd ed., Springer-Verlag, New York, 1982.

    Book  MATH  Google Scholar 

  2. I. C. Gohberg and M. G. Krein.Introduction to the Theory of Linear Nonselfadjoint OperatorsAmer. Math. Soc., Providence, RI, 1969.

    Google Scholar 

  3. L.E.FranksSignal Theory.Prentice Hall, Englewood Cliffs, NJ, 1969.

    Google Scholar 

  4. T. Kailath.Linear Systems. Prentice Hall, Englewood Cliffs, NJ, 1980.

    Google Scholar 

  5. L. R. Rabiner and R. W. Schafer.Digital Processing of Speech SignalsPrentice Hall, Englewood Cliffs, NJ, 1978.

    Google Scholar 

  6. S. H. Nawab and T. F. Quatieri. Short-time Fourier transform, inAdvanced Topics in Signal Processing(J. S. Lim and A. V. Oppenheim, eds.), Ch. 6, pp. 289–337, Prentice Hall, Englewood Cliffs, NJ, 1988.

    Google Scholar 

  7. L. B. Almeida and J. M. Tribolet. A spectral model for nonstationary voiced speech, inProc. IEEE ICASSP-82pp. 1303–1306, 1982.

    Google Scholar 

  8. W. Kozek and H. G. Feichtinger. Time-frequency structured decorrelation of speech signals via nonseparable Gabor frames, inProc. IEEE ICASSP-97Munich, Germany, pp. 1439–1442, April 1997.

    Google Scholar 

  9. P. A. Bello. Characterization of randomly time-variant linear channelsIEEE Trans. Comm. Syst. 11(1963), 360–393.

    Article  Google Scholar 

  10. K. A. Sostrand. Mathematics of the time-varying channelProc. NATO Advanced Study Inst. on Signal Processing with Emphasis on Underwater Acousticsvol. 2, pp. 25.1–25.20, 1968.

    Google Scholar 

  11. L. J. Ziomek. A scattering function approach to underwater acoustic detection and signal design, Technical Report TM 81–144, Pennsylvania State University, 1968.

    Google Scholar 

  12. R. S. Kennedy.Fading Dispersive Communication Channels.Wiley, New York, 1969.

    Google Scholar 

  13. J. G. Proakis.Digital Communications.3rd ed., McGraw-Hill, New York, 1995.

    Google Scholar 

  14. H. L. Van Trees.Detection Estimation and Modulation Theory Part III: Radar-Sonar Signal Processing and Gaussian Signals in NoiseKrieger, Malabar, FL, 1992.

    Google Scholar 

  15. J. D. Parsons.The Mobile Radio Propagation ChannelPentech Press, London, 1992.

    Google Scholar 

  16. G. W. Wornell. Spread-signature CDMA: Efficient multiuser communication in the presence of fadingIEEE Trans. Inform. Theory 41(1995), 1418–1438.

    Article  MATH  Google Scholar 

  17. A. M. Sayeed and B. Aazhang. Joint multipath—Doppler diversity in mobile wireless communicationsIEEE Trans. Comm. 47(1999), 123–132.

    Article  Google Scholar 

  18. D. König and J. E Böhme. Application of cyclostationary and time-frequency signal analysis to car engine diagnosis, inProc. IEEE ICASSP-94Adelaide, Australia, pp. 149–152, April 1994.

    Google Scholar 

  19. J. F. Böhme and D. König. Statistical processing of car engine signals for combustion diagnosis, inProc. IEEE-SP Workshop Stat. Signal and Array ProcessingQuebec, CA, pp. 369–374, June 1994.

    Google Scholar 

  20. H. L. Van Trees.Detection Estimation and Modulation Theory Part I: Detection Estimation and Linear Modulation TheoryWiley, New York, 1968.

    Google Scholar 

  21. F. Hlawatsch, G. Matz, H. Kirchauer, and W. Kozek. Time-frequency formulation, design, and implementation of time-varying optimal filters for signal estimationIEEE Trans. Signal Process.(2000), to appear.

    Google Scholar 

  22. H. Kirchauer, F. Hlawatsch, and W. Kozek. Time-frequency formulation and design of nonstationary Wiener filters, inProc. IEEE ICASSP-95Detroit, MI, pp. 1549–1552, May 1995.

    Google Scholar 

  23. J. A. Sills and E. W. Kamen. Time-varying matched filtersCircuits Systems Signal Process. 15(1996), 609–630.

    MATH  Google Scholar 

  24. J. A. Sills and E. W. Kamen. Wiener filtering of nonstationary signals based on spectral density functions, inProc. 34th IEEE Conf. Decision and ControlKobe, Japan, pp. 2521–2526, Dec. 1995.

    Google Scholar 

  25. G. Matz and F. Hlawatsch. Time-frequency formulation and design of optimal detectors, inProc. IEEE-SP Int. Sympos. Time-Frequency Time-Scale AnalysisParis, France, pp. 213–216, June 1996.

    Google Scholar 

  26. G. Matz and F. Hlawatsch. Time-frequency methods for signal detection with application to the detection of knock in car engines, inProc. IEEE-SP Workshop on Statistical Signal and Array Proc.Portland, OR, pp. 196–199, Sept. 1998.

    Google Scholar 

  27. A. M. Sayeed and D. L. Jones. Optimal detection using bilinear time-frequency and time-scale representationsIEEE Trans. Signal Process. 43(1995), 2872–2883.

    Google Scholar 

  28. A. M. Sayeed, P. Lander, and D. L. Jones. Improved time-frequency filtering of signal-averaged electrocardiogramsJ. Electrocardiology 28(1995), 53–58.

    Google Scholar 

  29. G. Matz and F. Hlawatsch. Minimax robust time-frequency filters for nonstationary signal estimation, inProc. IEEE ICASSP-99Phoenix, AZ, pp. 1333–1336, March 1999.

    Google Scholar 

  30. L. A. Zadeh. Frequency analysis of variable networksProc. IRE 76(1950), 291–299.

    Article  Google Scholar 

  31. T. A. C. M. Claasen and W. F. G. Mecklenbräuker. On stationary linear time-varying systemsIEEE Trans. Circuits Systems 29(1982), 169–184.

    Article  MATH  Google Scholar 

  32. J. J. Kohn and L. Nirenberg. An algebra of pseudo-differential operatorsComm. Pure Appl. Math. 18(1965), 269–305.

    Article  MathSciNet  MATH  Google Scholar 

  33. G.B.Folland.Harmonic Analysis in Phase Spacevol. 122 of Annals of Mathematics Studies, Princeton University Press, Princeton, NJ, 1989.

    Google Scholar 

  34. A. J. E. M. Janssen. Wigner weight functions and Weyl symbols of non-negative definite linear operatorsPhilips J. Research 44(1989), 7–42.

    MATH  Google Scholar 

  35. W. Kozek. Time-frequency signal processing based on the Wigner—Weyl frameworkSignal Process. 29(1992), 77–92.

    Article  MATH  Google Scholar 

  36. W. Kozek. On the generalized Weyl correspondence and its application to time-frequency analysis of linear time-varying systems, inProc. IEEE-SP Int. Sympos. Time-Frequency Time-Scale AnalysisVictoria, Canada, pp. 167170, Oct. 1992.

    Google Scholar 

  37. R. G. Shenoy and T. W. Parks. The Weyl correspondence and time-frequency analysisIEEE Trans. Signal Process. 42(1994), 318–331.

    Google Scholar 

  38. G. Matz and F. Hlawatsch. Time-frequency transfer function calculus (symbolic calculus) of linear time-varying systems (linear operators) based on a generalized underspread theoryJ. Math. Phys. Special Issue on Wavelet and Time-Frequency Analysis 39(1998), 4041–4071.

    MathSciNet  MATH  Google Scholar 

  39. T. A. C. M. Claasen and W. F. G. Mecklenbräuker. The Wigner distribution—A tool for time-frequency signal analysis; Part I: Continuous-time signals, Part II: Discrete-time signals, Part III: Relations with other time-frequency signal transformationsPhilips J. Res. 35(1980), 217–250, 276–300, and 372–389.

    Google Scholar 

  40. W. Mecklenbräuker and E Hlawatsch, eds.The Wigner Distribution—Theory and Applications in Signal ProcessingElsevier, Amsterdam, 1997.

    Google Scholar 

  41. P. Flandrin.Time-Frequency/Time-Scale AnalysisAcademic Press, San Diego, CA, 1999.

    Google Scholar 

  42. T. A. C. M. Claasen and W. F. G. Mecklenbräuker. On the time-frequency discriminiation of energy distributions: Can they look sharper than Heisenberg?, inProc. IEEE ICASSP-84San Diego, CA, pp. 41B7.1–41B7.4, 1984.

    Google Scholar 

  43. G. B. Folland and A. Sitaram. The uncertainty principle: A mathematical surveyJ. Fourier Anal. Appl. 3(1997), 207–238.

    Article  MathSciNet  MATH  Google Scholar 

  44. N. G. de Bruijn. Uncertainty principles in Fourier analysis, inInequalities(O. Shisha, ed.), pp. 57–71, Academic Press, New York, 1967.

    Google Scholar 

  45. A. J. E. M. Janssen.Positivity and spread of bilinear time-frequency distributionsinThe Wigner Distribution—Theory and Applications in Signal Processing(W. Mecklenbräuker and F. Hlawatsch, eds.), pp. 1–58, Elsevier, Amsterdam, 1997.

    Google Scholar 

  46. M. J. Bastiaans. Application of the Wigner distribution function in optics, inThe Wigner Distribution—Theory and Applications in Signal Processing(W. Mecklenbräuker and F. Hlawatsch, eds.), pp. 375–424, Elsevier, Amsterdam, 1997.

    Google Scholar 

  47. B. V. K. Kumar and K. J. deVos. Linear system description using Wigner distribution functions, inProc. SPIE Advanced Algorithms and Architectures for Signal Processing II 826(1987), 115–124.

    Google Scholar 

  48. F. Hlawatsch. Wigner distribution analysis of linear, time-varying systems, inProc. IEEE ISCAS-92San Diego, CA, pp. 1459–1462, May 1992.

    Google Scholar 

  49. W. Kozek. On the transfer function calculus for underspread LTV channelsIEEE Trans. Signal Process. 45(1997), 219–223.

    Article  Google Scholar 

  50. W. Kozek. Matched Weyl¨CHeisenberg Expansions of Nonstationary Environments. PhD thesis, Vienna University of Technology, March 1997.

    Google Scholar 

  51. W. Kozek. Adaptation of Weyl–CHeisenberg frames to underspread environments, inGabor Analysis and Algorithms: Theory and Applications(H. G. Feichtinger and T. Strohmer, eds.), Ch. 10, pp. 323–352, Birkhäuser, Boston, MA, 1998.

    Google Scholar 

  52. F. Hlawatsch and P. Flandrin. The interference structure of the Wigner distribution and related time-frequency signal representations, inThe Wigner Distribution–Theory and Applications in Signal Processing(W. Mecklenbräuker and F. Hlawatsch, eds.), pp. 59–133, Elsevier, Amsterdam, 1997.

    Google Scholar 

  53. F. Hlawatsch and G. F. Boudreaux-Bartels. Linear and quadratic time-frequency signal representationsIEEE Signal Process. Magazine 9(1992), 21–67.

    Article  Google Scholar 

  54. F. Hlawatsch and W. Kozek. The Wigner distribution of a linear signal spaceIEEE Trans. Signal Process. 41(1993), 1248–1258.

    Article  MATH  Google Scholar 

  55. F. Hlawatsch and W. Kozek. Time-frequency projection filters and time-frequency signal expansionsIEEE Trans. Signal Process. 42(1994), 3321–3334.

    Article  Google Scholar 

  56. F Hlawatsch.Time-Frequency Analysis and Synthesis of Linear Signal Spaces: Time-Frequency Filters Signal Detection and Estimation and Range¨CDoppler Estimation.Kluwer Academic, Boston, 1998.

    Google Scholar 

  57. A. J. E. M. Janssen. On the locus and spread of pseudo-density functions in the time-frequency planePhilips J. Res. 37(1982), 79–110.

    MathSciNet  MATH  Google Scholar 

  58. W. Martin and P. Flandrin. Wigner—CVille spectral analysis of nonstationary processesIEEE Trans. Acoust. Speech.Signal Process. 33(1985), 1461–1470.

    Article  Google Scholar 

  59. P. Flandrin. Time-dependent spectra for nonstationary stochastic processes, inTime and Frequency Representation of Signals and Systems(G. Longo and B. Picinbono, eds.), pp. 69–124, Springer-Verlag, Wien, 1989.

    Google Scholar 

  60. P. Flandrin and W. Martin. The Wigner¨CVille spectrum of nonstationary random signals, inThe Wigner Distribution—Theory and Applications in Signal Processing(W. Mecklenbräuker and F. Hlawatsch, eds.), pp. 211–267, Elsevier, Amsterdam, 1997.

    Google Scholar 

  61. G. Matz and E Hlawatsch. Time-varying spectra for underspread and overspread nonstationary processes, inProc. 32nd Asilomar Conf. Signals Systems ComputersPacific Grove, CA, pp. 282–286, Nov. 1998.

    Google Scholar 

  62. F Hlawatsch and W. Kozek. Time-frequency weighting and displacement effects in linear, time-varying systems, inProc. IEEE ISCAS-92San Diego, CA, pp. 1455–1458, May 1992.

    Google Scholar 

  63. F Hlawatsch. Regularity and unitarity of bilinear time-frequency signal representationsIEEE Trans. Inform. Theory 38(1992), 82–94.

    Article  MATH  Google Scholar 

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Hlawatsch, F., Matz, G. (2001). Quadratic Time-Frequency Analysis of Linear Time-Varying Systems. In: Debnath, L. (eds) Wavelet Transforms and Time-Frequency Signal Analysis. Applied and Numerical Harmonic Analysis. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-0137-3_9

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  • DOI: https://doi.org/10.1007/978-1-4612-0137-3_9

  • Publisher Name: Birkhäuser, Boston, MA

  • Print ISBN: 978-1-4612-6629-7

  • Online ISBN: 978-1-4612-0137-3

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