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Subspace Learning of Neural Networks (Automation and Control Engineering)

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Book News Annotation:

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. Annotation ©2010 Book News, Inc., Portland, OR (booknews.com)

Synopsis:

"Using real-life examples to illustrate the performance of learning algorithms and instructing readers how to apply them to practical applications, this work offers a comprehensive treatment of subspace learning algorithms for neural networks. The authors summarize a decade of high quality research offering a host of practical applications. They demonstrate ways to extend the use of algorithms to fields such as encryption communication, data mining, computer vision, and signal and image processing to name just a few. The brilliance of the work lies with how it coherently builds a theoretical understanding of the convergence behavior of subspace learning algorithms through a summary of chaotic behaviors"--

Product Details

ISBN:
9781439815359
Author:
Cheng, Jian
Publisher:
CRC Press
Author:
Zhou, Jiliu
Author:
Yi, Zhang
Subject:
General-General
Subject:
Computers-Reference - General
Series:
Automation and Control Engineering
Publication Date:
20100931
Binding:
Hardcover
Language:
English
Pages:
248

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Computers and Internet » Networking » General
Reference » Science Reference » Technology
Science and Mathematics » Chemistry » Chemical Engineering
Science and Mathematics » Electricity » General Electricity
Science and Mathematics » Electricity » General Electronics

Subspace Learning of Neural Networks (Automation and Control Engineering) New Hardcover
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Product details 248 pages CRC Press - English 9781439815359 Reviews:
"Synopsis" by , "Using real-life examples to illustrate the performance of learning algorithms and instructing readers how to apply them to practical applications, this work offers a comprehensive treatment of subspace learning algorithms for neural networks. The authors summarize a decade of high quality research offering a host of practical applications. They demonstrate ways to extend the use of algorithms to fields such as encryption communication, data mining, computer vision, and signal and image processing to name just a few. The brilliance of the work lies with how it coherently builds a theoretical understanding of the convergence behavior of subspace learning algorithms through a summary of chaotic behaviors"--
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