Robust Time-Frequency Distributions with Complex-Lag Argument

The robust time-frequency distributions with complex-lag argument are proposed. They can provide an accurate estimation of fast varying instantaneous frequency in the presence of noise with heavy-tailed probability density function. The L-estimate form of this distribution is defined and it includes the L-estimate form of Wigner distribution as a special case. A modification for multicomponent signal representation is proposed, as well. Theoretical considerations are illustrated by the examples.

[1]  Thippur V. Sreenivas,et al.  IF estimation using higher order TFRs , 2002, Signal Process..

[2]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals , 1992, Proc. IEEE.

[3]  LJubisa Stankovic,et al.  Median filter based realizations of the robust time-frequency distributions , 2001, Signal Process..

[4]  Igor Djurovic,et al.  Robust time-frequency distributions , 2001, Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467).

[5]  Ta-Hsin Li,et al.  Estimation of the Parameters of Sinusoidal Signals in Non-Gaussian Noise , 2009, IEEE Transactions on Signal Processing.

[6]  Cornel Ioana,et al.  Effects of Cauchy Integral Formula Discretization on the Precision of IF Estimation: Unified Approach to Complex-Lag Distribution and its Counterpart L-Form , 2009, IEEE Signal Processing Letters.

[7]  Srdjan Stankovic,et al.  Introducing time-frequency distribution with a 'complex-time' argument , 1996 .

[8]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[9]  F. Hlawatsch,et al.  Linear and quadratic time-frequency signal representations , 1992, IEEE Signal Processing Magazine.

[10]  V. Katkovnik,et al.  Instantaneous Frequency Estimation Using Robust Spectrogram with Varying Window Length , 2011 .

[11]  Ljubisa Stankovic,et al.  A method for time-frequency analysis , 1994, IEEE Trans. Signal Process..

[12]  Irena Orovic,et al.  A Class of Highly Concentrated Time-Frequency Distributions Based on the Ambiguity Domain Representation and Complex-Lag Moment , 2009, EURASIP J. Adv. Signal Process..

[13]  Boualem Boashash,et al.  Complex-lag polynomial Wigner-Ville distribution , 1997, TENCON '97 Brisbane - Australia. Proceedings of IEEE TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications (Cat. No.97CH36162).

[14]  Ljubisa Stankovic,et al.  Time-frequency distributions with complex argument , 2002, IEEE Trans. Signal Process..

[15]  Cornel Ioana,et al.  General form of time-frequency distribution with complex-lag argument , 2008 .

[16]  Vladimir Katkovnik.  Robust M-periodogram , 1998, IEEE Trans. Signal Process..

[17]  Cornel Ioana,et al.  Generalized Representation of Phase Derivatives for Regular Signals , 2007, IEEE Transactions on Signal Processing.

[18]  LJubisa Stankovic,et al.  Robust Wigner distribution with application to the instantaneous frequency estimation , 2001, IEEE Trans. Signal Process..

[19]  Braham Barkat,et al.  Robust time-frequency distributions based on the robust short time fourier transform , 2005, Ann. des Télécommunications.

[20]  Igor Djurovic,et al.  Robust L-estimation based forms of signal transforms and time-frequency representations , 2003, IEEE Trans. Signal Process..