Presentation | 1997/6/27 Effect of the updating block size on ICA algorithms Allan Kardec Barros, Hani Yehia, Noboru Ohnishi, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Independent component analysis (ICA) is a new kind of algorithm used for separating mixed sources. Here we study the influence of the updating block size on the convergence of ICA algorithms, for stationary and non-stationary data. We found that ICA algorithms with a small enough number of observations: a) do not necessarily converge to a solution which cancels the mixing effect; b) depend on the initial estimated parameters; c) separate more than one Gaussian source. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | blind separation / independent component analysis / batch update / Gaussian signals |
Paper # | CAS97-24 |
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Committee | DSP |
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Conference Date | 1997/6/27(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Digital Signal Processing (DSP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Effect of the updating block size on ICA algorithms |
Sub Title (in English) | |
Keyword(1) | blind separation |
Keyword(2) | independent component analysis |
Keyword(3) | batch update |
Keyword(4) | Gaussian signals |
1st Author's Name | Allan Kardec Barros |
1st Author's Affiliation | Graduate School of Engineering, Nagoya University() |
2nd Author's Name | Hani Yehia |
2nd Author's Affiliation | ATR Human Information Lab. |
3rd Author's Name | Noboru Ohnishi |
3rd Author's Affiliation | Graduate School of Engineering, Nagoya University:RIKEN BMC Research Center |
Date | 1997/6/27 |
Paper # | CAS97-24 |
Volume (vol) | vol.97 |
Number (no) | 141 |
Page | pp.pp.- |
#Pages | 4 |
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