| Presentation | 2001/12/14 Blind Separation Using Adaptive Nonlinear Functions Controlled by Kurtosis Takayuki Sakai, Kenji Nakayama, Akihiro Hirano, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | 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 κ_4. It was suggested that than y and y^3, where y is the output, are useful nonlinear functions for super-Gaussian(κ_4>0)and sub-Gaussian(κ_4<0), respectively. In this paper, an adaptive nonlinear function is proposed. It has a form of f(y)=a tanh y+(1-a)y^3/4, where a is controlled by kurtosis. It is assumed that the pdf p(y)of the output signal y satisfies the stability condition f(y)=(dp(y)/dy)/p(y). Based on this assumption, the parameter a and the kurtosis is related. First, the kurtosis is calculated for given a, which takes value in 0≤a≤1. Next, this numerical relation is approximated by a function a=q(κ_4). In a learning process, κ_4(n)of the output signals is calculated at each sample n, and a is determined by a(n)=q(κ_4(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 y^3 based on polarity of κ_4(n). |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Blind separation / Nonlinear functions / Kurtosis / Stabilization / Learning |
| Paper # | NC2001-79 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2001/12/14(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Blind Separation Using Adaptive Nonlinear Functions Controlled by Kurtosis |
| Sub Title (in English) | |
| Keyword(1) | Blind separation |
| Keyword(2) | Nonlinear functions |
| Keyword(3) | Kurtosis |
| Keyword(4) | Stabilization |
| Keyword(5) | Learning |
| 1st Author's Name | Takayuki Sakai |
| 1st Author's Affiliation | Division of Electronics and Computer Science, Graduate School of Natural Science and Technology Dept.of Information and Systems Eng.Faculty of Eng.Kanazawa University() |
| 2nd Author's Name | Kenji Nakayama |
| 2nd Author's Affiliation | Dept.of Information and Systems Eng.Faculty of Eng.Kanazawa University |
| 3rd Author's Name | Akihiro Hirano |
| 3rd Author's Affiliation | Dept.of Information and Systems Eng.Faculty of Eng.Kanazawa University |
| Date | 2001/12/14 |
| Paper # | NC2001-79 |
| Volume (vol) | vol.101 |
| Number (no) | 534 |
| Page | pp.pp.- |
| #Pages | 8 |
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