Proceedings of the Korean Information Science Society Conference (한국정보과학회:학술대회논문집)
- 2002.04b
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- Pages.289-291
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- 2002
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- 1598-5164(pISSN)
Second-order nonstationary source separation; Natural gradient learning
2차 Nonstationary 신호 분리: 자연기울기 학습
Abstract
Host of source separation methods focus on stationary sources so higher-order statistics is necessary In this paler we consider a problem of source separation when sources are second-order nonstationary stochastic processes . We employ the natural gradient method and develop learning algorithms for both 1inear feedback and feedforward neural networks. Thus our algorithms possess equivariant property Local stabi1iffy analysis shows that separating solutions are always locally stable stationary points of the proposed algorithms, regardless of probability distributions of
Keywords