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Subspace learning of neural networks.

9781439815359

Subspace learning of neural networks.

Lv, Jian Cheng et al.

CRC Press

2011

233 pages

$99.95

Hardcover

Automation and control engineering

QA76.87

Lv et al. (Sichuan U., China) focus on the convergence analysis of subspace learning algorithms of neural networks and the ways to extend the use of these networks in fields like biomedical signal processing, biomedical image processing, and surface fitting. Using the discrete determination time (DDT) method, they consider invariant sets and global boundedness of some algorithms, their convergence conditions, the relationship between a stochastic discrete time algorithm and the corresponding DDT algorithm using block algorithms, and the chaotic and robust properties of algorithms. The book is meant for postgraduates, engineers, researchers, and those working in data mining, image processing, and signal processing.

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Publication:SciTech Book News
Article Type:Book review
Date:Dec 1, 2010
Words:135
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