An Information Theoretic Approach to Neural Computing is popular PDF and ePub book, written by Gustavo Deco in 2012-12-06, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, An Information Theoretic Approach to Neural Computing can be Read Online from any device for your convenience.
An Information Theoretic Approach to Neural Computing Book PDF Summary
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 particular 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.
Detail Book of An Information Theoretic Approach to Neural Computing PDF
- Author : Gustavo Deco
- Release : 06 December 2012
- Publisher : Springer Science & Business Media
- ISBN : 9781461240167
- Genre : Computers
- Total Page : 265 pages
- Language : English
- PDF File Size : 17,7 Mb
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