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Titlebook: An Information-Theoretic Approach to Neural Computing; Gustavo Deco,Dragan Obradovic Book 1996 Springer-Verlag New York, Inc. 1996 calculu

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樓主: 人工合成
11#
發(fā)表于 2025-3-23 13:22:15 | 只看該作者
Die Prognose der Essentiellen HypertonieThe statistical theory of infinite ensemble of networks with fixed parameters was discussed in the previous chapter. The posteriori distribution on the ensemble was determined by maximizing the ensemble entropy. Consequently, the learning in such an ensemble model was reduced to determination of the best temperature.
12#
發(fā)表于 2025-3-23 13:53:11 | 只看該作者
13#
發(fā)表于 2025-3-23 20:25:49 | 只看該作者
Independent Component Analysis: General Formulation and Linear CaseThis chapter formulates the problem of . (ICA) as a search for an information-preserving linear mapping which results in statistically independent output components. The mathematical tools used herein originate from information theory and statistical analysis.
14#
發(fā)表于 2025-3-24 02:08:19 | 只看該作者
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發(fā)表于 2025-3-24 03:59:44 | 只看該作者
An Information-Theoretic Approach to Neural Computing978-1-4612-4016-7Series ISSN 1431-6854
16#
發(fā)表于 2025-3-24 08:21:24 | 只看該作者
17#
發(fā)表于 2025-3-24 14:27:30 | 只看該作者
Perspectives in Neural Computinghttp://image.papertrans.cn/a/image/155053.jpg
18#
發(fā)表于 2025-3-24 17:44:18 | 只看該作者
https://doi.org/10.1007/978-1-4612-4016-7calculus; complex system; control; information theory; learning; neural networks; supervised learning
19#
發(fā)表于 2025-3-24 20:37:55 | 只看該作者
20#
發(fā)表于 2025-3-25 02:54:05 | 只看該作者
G. Bi?rck,G. Blomqvist,J. Sieversfor modeling and control of nonlinear and complex systems. The ability of neural networks to extract dependencies from measured data and complement the existing analytic knowledge of the underlying phenomena makes them a valuable tool in addressing a wide range of applications. The interaction betwe
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