Blind separation of nonstationary sources based on spatial time-frequency distributions
EURASIP Journal on Applied Signal Processing
Blind source separation based on constant modulus criterion and signal mutual information
Computers and Electrical Engineering
A Novel Algorithm for BSS of Frequency-Hopping Signals Based on Time Frequency Ratio
ICISE '09 Proceedings of the 2009 First IEEE International Conference on Information Science and Engineering
Underdetermined blind separation of non-sparse sources using spatial time-frequency distributions
Digital Signal Processing
A Modified Approach of Underdetermined Blind Source Separation in Time-Frequency Domain
NSWCTC '10 Proceedings of the 2010 Second International Conference on Networks Security, Wireless Communications and Trusted Computing - Volume 01
Two time-frequency ratio-based blind source separation methods for time-delayed mixtures
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Contrast functions for blind source separation based on time-frequency information-theory
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Kernel design for reduced interference distributions
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A high-resolution quadratic time-frequency distribution formulticomponent signals analysis
IEEE Transactions on Signal Processing
Blind Source Separation in the Time-Frequency Domain Based on Multiple Hypothesis Testing
IEEE Transactions on Signal Processing
Blind source separation based on time-frequency signalrepresentations
IEEE Transactions on Signal Processing
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Blind source separation (BSS) based on time-frequency distributions (TFDs) exploits the underlying diagonal or off-diagonal structure of TFD matrices to separate the source signals. In this paper, we propose a new signal-independent kernel which is defined in both the time-lag and the Doppler-lag domain and satisfies most of the desirable properties of a TFD. The main objective of this research is to achieve the high resolution and the maximum cross-term reduction with the preferable diagonal or off-diagonal structure of TFD matrices in BSS applications. Moreover, a BSS approach is developed which includes first whitening mixed signals, then constructing a set of TFD matrices using the proposed TFD and the Hough transform, finally a joint diagonalization of a combined set of TFD matrices to estimate the mixing matrix and the source signals. By use of the techniques proposed in this paper, the improved performance of BSS of nonstationary signals has been achieved.