Subspace learning of neural networks /

"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 rese...

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Bibliographic Details
Main Author: Lv, Jian Cheng
Corporate Author: Taylor & Francis
Other Authors: Yi, Zhang, Zhou, Jiliu
Format: eBook
Language:English
Published: Boca Raton, FL : CRC Press, ©2011.
Series:Automation and control engineering.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:"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"--
Physical Description:1 online resource (xxii, 233 pages) : illustrations
Bibliography:Includes bibliographical references (pages 213-228) and index.
ISBN:1322612161
9781322612164
9781315218120
1315218127
9781439815366
1439815364
9781351825320
1351825321