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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
A. W. Naylor and G. R. Sell.Linear Operator Theory in Engineering and Science2nd ed., Springer-Verlag, New York, 1982.
I. C. Gohberg and M. G. Krein.Introduction to the Theory of Linear Nonselfadjoint OperatorsAmer. Math. Soc., Providence, RI, 1969.
L.E.FranksSignal Theory.Prentice Hall, Englewood Cliffs, NJ, 1969.
T. Kailath.Linear Systems. Prentice Hall, Englewood Cliffs, NJ, 1980.
L. R. Rabiner and R. W. Schafer.Digital Processing of Speech SignalsPrentice Hall, Englewood Cliffs, NJ, 1978.
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.
L. B. Almeida and J. M. Tribolet. A spectral model for nonstationary voiced speech, inProc. IEEE ICASSP-82pp. 1303–1306, 1982.
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.
P. A. Bello. Characterization of randomly time-variant linear channelsIEEE Trans. Comm. Syst. 11(1963), 360–393.
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.
L. J. Ziomek. A scattering function approach to underwater acoustic detection and signal design, Technical Report TM 81–144, Pennsylvania State University, 1968.
R. S. Kennedy.Fading Dispersive Communication Channels.Wiley, New York, 1969.
J. G. Proakis.Digital Communications.3rd ed., McGraw-Hill, New York, 1995.
H. L. Van Trees.Detection Estimation and Modulation Theory Part III: Radar-Sonar Signal Processing and Gaussian Signals in NoiseKrieger, Malabar, FL, 1992.
J. D. Parsons.The Mobile Radio Propagation ChannelPentech Press, London, 1992.
G. W. Wornell. Spread-signature CDMA: Efficient multiuser communication in the presence of fadingIEEE Trans. Inform. Theory 41(1995), 1418–1438.
A. M. Sayeed and B. Aazhang. Joint multipath—Doppler diversity in mobile wireless communicationsIEEE Trans. Comm. 47(1999), 123–132.
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.
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.
H. L. Van Trees.Detection Estimation and Modulation Theory Part I: Detection Estimation and Linear Modulation TheoryWiley, New York, 1968.
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.
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.
J. A. Sills and E. W. Kamen. Time-varying matched filtersCircuits Systems Signal Process. 15(1996), 609–630.
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.
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.
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.
A. M. Sayeed and D. L. Jones. Optimal detection using bilinear time-frequency and time-scale representationsIEEE Trans. Signal Process. 43(1995), 2872–2883.
A. M. Sayeed, P. Lander, and D. L. Jones. Improved time-frequency filtering of signal-averaged electrocardiogramsJ. Electrocardiology 28(1995), 53–58.
G. Matz and F. Hlawatsch. Minimax robust time-frequency filters for nonstationary signal estimation, inProc. IEEE ICASSP-99Phoenix, AZ, pp. 1333–1336, March 1999.
L. A. Zadeh. Frequency analysis of variable networksProc. IRE 76(1950), 291–299.
T. A. C. M. Claasen and W. F. G. Mecklenbräuker. On stationary linear time-varying systemsIEEE Trans. Circuits Systems 29(1982), 169–184.
J. J. Kohn and L. Nirenberg. An algebra of pseudo-differential operatorsComm. Pure Appl. Math. 18(1965), 269–305.
G.B.Folland.Harmonic Analysis in Phase Spacevol. 122 of Annals of Mathematics Studies, Princeton University Press, Princeton, NJ, 1989.
A. J. E. M. Janssen. Wigner weight functions and Weyl symbols of non-negative definite linear operatorsPhilips J. Research 44(1989), 7–42.
W. Kozek. Time-frequency signal processing based on the Wigner—Weyl frameworkSignal Process. 29(1992), 77–92.
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.
R. G. Shenoy and T. W. Parks. The Weyl correspondence and time-frequency analysisIEEE Trans. Signal Process. 42(1994), 318–331.
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.
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.
W. Mecklenbräuker and E Hlawatsch, eds.The Wigner Distribution—Theory and Applications in Signal ProcessingElsevier, Amsterdam, 1997.
P. Flandrin.Time-Frequency/Time-Scale AnalysisAcademic Press, San Diego, CA, 1999.
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.
G. B. Folland and A. Sitaram. The uncertainty principle: A mathematical surveyJ. Fourier Anal. Appl. 3(1997), 207–238.
N. G. de Bruijn. Uncertainty principles in Fourier analysis, inInequalities(O. Shisha, ed.), pp. 57–71, Academic Press, New York, 1967.
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.
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.
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.
F. Hlawatsch. Wigner distribution analysis of linear, time-varying systems, inProc. IEEE ISCAS-92San Diego, CA, pp. 1459–1462, May 1992.
W. Kozek. On the transfer function calculus for underspread LTV channelsIEEE Trans. Signal Process. 45(1997), 219–223.
W. Kozek. Matched Weyl¨CHeisenberg Expansions of Nonstationary Environments. PhD thesis, Vienna University of Technology, March 1997.
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.
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.
F. Hlawatsch and G. F. Boudreaux-Bartels. Linear and quadratic time-frequency signal representationsIEEE Signal Process. Magazine 9(1992), 21–67.
F. Hlawatsch and W. Kozek. The Wigner distribution of a linear signal spaceIEEE Trans. Signal Process. 41(1993), 1248–1258.
F. Hlawatsch and W. Kozek. Time-frequency projection filters and time-frequency signal expansionsIEEE Trans. Signal Process. 42(1994), 3321–3334.
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.
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.
W. Martin and P. Flandrin. Wigner—CVille spectral analysis of nonstationary processesIEEE Trans. Acoust. Speech.Signal Process. 33(1985), 1461–1470.
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.
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.
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.
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.
F Hlawatsch. Regularity and unitarity of bilinear time-frequency signal representationsIEEE Trans. Inform. Theory 38(1992), 82–94.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer Science+Business Media New York
About this chapter
Cite this chapter
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
Download citation
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
eBook Packages: Springer Book Archive