Art

J-GLOBAL ID：200902131072173774   Reference number：99A0740666

Information Theory, Statistics, and Machine Learning. Applying ICA on Signal Processing.

情報理論・統計手法と学習技術 独立成分解析の信号処理への応用

Author (1)： IKEDA SHIRO (科学技術振興事業団)
Material： 計測と制御  (Journal of the Society of Instrument and Control Engineers)
Volume： 38  Issue： 7  Page： 461-467  Publication year： Jul. 10, 1999 
JST Material Number： F0131A  ISSN： 0453-4662  CODEN： KESEA  Document type： Article
Article type： 解説  Country of issue： Japan (JPN)  Language： JAPANESE (JA)

Thesaurus term： *signal analysis ,...

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JST classification (2)： Signal theory  (ND02020G) ,  Biometry and biometric analysis in geneyal  (EL03010R)

Reference (30)：

• AMARI, S. ICA of temporally correlated signals-learning algorithm. Proceedings of International Workshop on Independent Component Analysis and Blind Signal Separation (ICA '99). 1999, 13-18
• 甘利. 独立成分解析. Computer Today. 1998, 9月
• AMARI, S. Blind source separation-semiparametric statistical approach. IEEE Trans.Signal Processing. 1997, 45, 11, 2692-2700
• AMARI, S. Stability analysis of learning algorithms for blind source separation. Neural Networks. 1997, 10, 8, 1345-1351
• AMARI, S. A new learning algorigthm for blind signal separation. Advances in Neural Information Processing Systems. 1996, 8, 757-763

Terms in the title (5)： 情報理論 ,  統計手法 ,  学習 ,  独立成分解析 ,  応用