Neural networks and computing : learning algorithms and applications / Tommy W.S. Chow, Siu-Yeung Cho.

By:

Chow, Tommy W. S

Contributor(s):

Cho, Siu-Yeung

Material type: Text

TextSeries: Series in electrical and computer engineering ; v. 7.Publication details: London : Imperial College Press ; Singapore ; Hackensack, NJ : Distributed by World Scientific, 2007.Description: 1 online resource (xii, 309 pages) : illustrationsContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781860949692
186094969X
1281869457
9781281869456
9786611869458
661186945X

Subject(s): Genre/Form:

Electronic books.

Additional physical formats: Print version:: Neural networks and computing.DDC classification:

006.3/2 22

LOC classification:

QA76.87 .C48 2007eb

Online resources:

Click here to access online

Contents:

Introduction -- Learning performance and enhancement -- Generalization and performance enhancement -- Basis function networks for classification -- Self-organizing maps -- Classification and feature selection -- Engineering applications.

Summary: This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been covered by many existing books in this area. Additionally, the book highlights the important feature selection problem, which baffles many neural networks practitioners because of the difficulties handling large datasets. It also contains several interesting IT, engineering and bioinformatics applications.

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Holdings
Item type	Home library	Collection	Call number	Materials specified	Status	Date due	Barcode
Electronic-Books	OPJGU Sonepat- Campus	E-Books EBSCO			Available

Some online versions lack accompanying media packaged with the printed version.

Includes bibliographical references (pages 291-304) and index.

Print version record.

This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been covered by many existing books in this area. Additionally, the book highlights the important feature selection problem, which baffles many neural networks practitioners because of the difficulties handling large datasets. It also contains several interesting IT, engineering and bioinformatics applications.

English.

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