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    The Bone Clocks

    David Mitchell 9781400065677

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Other titles in the Intelligent Systems Reference Library series:

Intelligent Systems Reference Library #19: Intelligent Systems: Approximation by Artificial Neural Networks

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Intelligent Systems Reference Library #19: Intelligent Systems: Approximation by Artificial Neural Networks Cover

 

Synopses & Reviews

Publisher Comments:

This brief monograph is the first one to deal exclusively with the quantitative approximation by artificial neural networks to the identity-unit operator. Here we study with rates the approximation properties of the "right" sigmoidal and hyperbolic tangent artificial neural network positive linear operators. In particular we study the degree of approximation of these operators to the unit operator in the univariate and multivariate cases over bounded or unbounded domains. This is given via inequalities and with the use of modulus of continuity of the involved function or its higher order derivative. We examine the real and complex cases. For the convenience of the reader, the chapters of this book are written in a self-contained style. This treatise relies on author's last two years of related research work. Advanced courses and seminars can be taught out of this brief book. All necessary background and motivations are given per chapter. A related list of references is given also per chapter. The exposed results are expected to find applications in many areas of computer science and applied mathematics, such as neural networks, intelligent systems, complexity theory, learning theory, vision and approximation theory, etc. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also for all science libraries.

Synopsis:

This brief monograph is the first to deal exclusively with the quantitative approximation by artificial neural networks to the identity-unit operator. Each chapter is written in a self-contained style, with all necessary background and motivations included.

Table of Contents

Univariate sigmoidal neural network quantitative approximation.- Univariate hyperbolic tangent neural network quantitative approximation.- Multivariate sigmoidal neural network quantitative approximation.- Multivariate hyperbolic tangent neural network quantitative approximation.

Product Details

ISBN:
9783642214301
Author:
Anastassiou, George A.
Publisher:
Springer
Location:
Berlin, Heidelberg
Subject:
Mathematics-Applied
Subject:
Artificial Intelligence
Subject:
Computational intelligence
Subject:
intelligent systems
Subject:
Neural Networks
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
APPLICATIONS OF MATHEMATICS
Subject:
Engineering
Subject:
B
Subject:
Mathematics
Copyright:
Edition Description:
2011
Series:
Intelligent Systems Reference Library
Series Volume:
19
Publication Date:
20110607
Binding:
HARDCOVER
Language:
English
Pages:
116
Dimensions:
235 x 155 mm 760 gr

Related Subjects

Business » General
Business » Management
Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
History and Social Science » Economics » General
History and Social Science » Geography » General
Reference » Science Reference » Technology
Science and Mathematics » Environmental Studies » Environment
Science and Mathematics » Mathematics » Applied

Intelligent Systems Reference Library #19: Intelligent Systems: Approximation by Artificial Neural Networks New Hardcover
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Product details 116 pages Springer - English 9783642214301 Reviews:
"Synopsis" by , This brief monograph is the first to deal exclusively with the quantitative approximation by artificial neural networks to the identity-unit operator. Each chapter is written in a self-contained style, with all necessary background and motivations included.
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