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タイトル: An adaptive nonlinear function controlled by kurtosis for blind source separation
著者: Nakayama, Kenji link image
Hirano, Akihiro link image link image
Sakai, T.
中山, 謙二
平野, 晃宏
発行日: 2002年 5月
出版社(者): Institute of Electrical and Electronics Engineers (IEEE)
引用: Proceedings of the International Joint Conference on Neural Networks 2, pp. 1234-1239
雑誌名: Proceedings of the International Joint Conference on Neural Networks
巻: 26
開始ページ: 1234
終了ページ: 1239
抄録: In blind source separation, convergence and separation performances are highly dependent on a relation between probability density functions (pdf) of signal sources and nonlinear functions used in updating coefficients of a separation block. This relation was analyzed based on kurtosis κ4. It was suggested that tanh y and y3, where y is the output, are useful nonlinear functions for super-Gaussian (κ4 > 0) and sub-Gaussian (κ4 < 0), respectively. In this paper, an adaptive nonlinear function is proposed. It has a form of f(y) = a tanh y + (1 - a)y3/4, where a is controlled by the kurtosis of the output signal yκ(n). It is assumed that the pdf p(y) of the output signal satisfies the stability condition f(y) = -(dp(y)/dy)/p(y). Based on this assumption, the parameter a and the kurtosis is related. This relation approximated by a function a = q(κ4). In a learning process, κ4(n) of the output signal is calculated at each sample n, and a(n) is determined by a(n) = q(κ4(n)). Then, the nonlinear function f(y) is adjusted. Blind separation of music signals of 2-5 channels were simulated. The proposed method is superior to a method, which switches tanh y and y3 based on polarity of κ4(n).
URI: http://hdl.handle.net/2297/6886
資料種別: Conference Paper
版表示: publisher

このアイテムを引用あるいはリンクする場合は次の識別子を使用してください。 http://hdl.handle.net/2297/6886



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