Cluster Guide Particle Swarm Optimization (CGPSO) for Underdetermined Blind Source Separation With Advanced Conditions

The underdetermined blind source separation (BSS), which based on sparse representation, is discussed in this paper; moreover, some difficulties (or real assumptions) that were left out of consideration before are aimed. For instance, the number of sources, , is unknown, large-scale, or time-variant...

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Veröffentlicht in:	IEEE transactions on evolutionary computation 2011-12, Vol.15 (6), p.798-811
Hauptverfasser:	SUN, Tsung-Ying, LIU, Chan-Cheng, TSAI, Shang-Jeng, HSIEH, Sheng-Ta, LI, Kan-Yuan
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Blind source separation Cluster guide Clustering algorithms Computer science control theory systems Detection, estimation, filtering, equalization, prediction Exact sciences and technology Fourier transforms Information, signal and communications theory Optimization particle swarm optimization Sensors Signal and communications theory Signal, noise Sparse matrices sparse representation Telecommunications and information theory Theoretical computing underdetermined blind source separation (BSS) unknown number of source
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