An Novel Algorithm for Blind Source Separation with Unknown Sources Number
The natural gradient blind source separation (BSS) algorithm with unknown source number proposed by Cichocki in 1999 is justified in this paper. An new method to detect the redundant separated signals based on structure of separating matrix is proposed, by embedding it into the natural gradient algorithm, an novel BSS algorithm with an unknown source number is developed. The novel algorithm can successfully separate source signals and converge stably, while the Cichocki’s algorithm would diverge inevitably. The new method embedded in novel algorithm can detect and cancel the redundant separated signals within 320 iteration, which is far quicker than the method based on the decorrelation, if some parameters are chosen properly.
KeywordsMutual Information Independent Component Analysis Blind Source Separation Neural Computation Natural Gradient
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