Zero-Tracking Time-Frequency Distributions
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 3 - Volume 3
Renyi information and signal-dependent optimal kernel design
ICASSP '95 Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02
The robust Wigner distribution
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01
Auto-term representation by the reduced interference distributions: a procedure for kernel design
IEEE Transactions on Signal Processing
Analysis and synthesis of multicomponent signals using positivetime-frequency distributions
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Robust Wigner distribution with application to the instantaneousfrequency estimation
IEEE Transactions on Signal Processing
High spectral resolution time-frequency distribution kernels
IEEE Transactions on Signal Processing
Hybrid linear/quadratic time-frequency attributes
IEEE Transactions on Signal Processing
Toeplitz and Hankel kernels for estimating time-varying spectra ofdiscrete-time random processes
IEEE Transactions on Signal Processing
An adaptive optimal-kernel time-frequency representation
IEEE Transactions on Signal Processing
Kernel design for time-frequency signal analysis using the Radontransform
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
Time--frequency feature representation using energy concentration: An overview of recent advances
Digital Signal Processing
An overview of the adaptive robust DFT
EURASIP Journal on Advances in Signal Processing - Special issue on robust processing of nonstationary signals
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Estimation of the instantaneous frequency (IF) in a high noise environment, by using the Wigner distribution (WD), is considered. In this case the error is of impulse nature. An algorithm for the IF estimation, which combines the nonparametric method based on the WD maxima with the minimization of the IF variations between consecutive points, is proposed. The off-line and on-line realizations are presented. The on-line realization is an instance of the (generalized) Viterbi algorithm. Application of this algorithm on the monocomponent and multicomponent frequency modulated signals is demonstrated. For multicomponent signals, the algorithm is applied on other (reduced interference) distributions. Numerical examples, including statistical study of the algorithm performance, are given.