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<図書>
An information-theoretic approach to neural computing

責任表示 Gustavo Deco, Dragan Obradovic
シリーズ Perspectives in neural computing
データ種別 図書
出版者 New York : Springer
出版年 c1996
本文言語 英語
大きさ xiii, 261 p. : ill. ; 25 cm
概要 A detailed formulation of neural networks from the information-theoretic viewpoint. The authors show how this perspective provides new insights into the design theory of neural networks. In particula... they demonstrate how these methods may be applied to the topics of supervised and unsupervised learning, including feature extraction, linear and non-linear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural networks, but all the relevant concepts from information theory are carefully introduced and explained. Consequently, readers from varied scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this an extremely valuable introduction to this topic. 続きを見る

所蔵情報


理系図1F 開架 072032195008785 401/D52 1996

芸工2階 072032196000116 401/D52/a 1996

書誌詳細

一般注記 Includes bibliographical references (p. [243]-257) and index
著者標目 *Deco, Gustavo
Obradovic, Dragan
件 名 LCSH:Neural networks (Computer science)
分 類 DC20:006.3
書誌ID 1000921160
ISBN 0387946667
NCID BA27274474
巻冊次 ISBN:0387946667
登録日 2009.09.16
更新日 2009.09.17

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