Neural Computing An Introduction

Author : R Beale,T Jackson
Publisher : CRC Press
Page : 260 pages
File Size : 43,6 Mb
Release : 1990-01-01
Category : Mathematics
ISBN : 1420050435

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Neural Computing - An Introduction by R Beale,T Jackson Pdf

Neural computing is one of the most interesting and rapidly growing areas of research, attracting researchers from a wide variety of scientific disciplines. Starting from the basics, Neural Computing covers all the major approaches, putting each in perspective in terms of their capabilities, advantages, and disadvantages. The book also highlights the applications of each approach and explores the relationships among models developed and between the brain and its function. A comprehensive and comprehensible introduction to the subject, this book is ideal for undergraduates in computer science, physicists, communications engineers, workers involved in artificial intelligence, biologists, psychologists, and physiologists.

Author : John A. Hertz
Publisher : CRC Press
Page : 352 pages
File Size : 53,9 Mb
Release : 2018-03-08
Category : Science
ISBN : 9780429968211

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Introduction To The Theory Of Neural Computation by John A. Hertz Pdf

Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.

Author : James A. Anderson
Publisher : MIT Press
Page : 680 pages
File Size : 46,9 Mb
Release : 1995
Category : Computers
ISBN : 0262510812

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An Introduction to Neural Networks by James A. Anderson Pdf

An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modeling, and at engineers who want to go beyond formal algorithms to applications and computing strategies. It is the only current text to approach networks from a broad neuroscience and cognitive science perspective, with an emphasis on the biology and psychology behind the assumptions of the models, as well as on what the models might be used for. It describes the mathematical and computational tools needed and provides an account of the author's own ideas. Students learn how to teach arithmetic to a neural network and get a short course on linear associative memory and adaptive maps. They are introduced to the author's brain-state-in-a-box (BSB) model and are provided with some of the neurobiological background necessary for a firm grasp of the general subject. The field now known as neural networks has split in recent years into two major groups, mirrored in the texts that are currently available: the engineers who are primarily interested in practical applications of the new adaptive, parallel computing technology, and the cognitive scientists and neuroscientists who are interested in scientific applications. As the gap between these two groups widens, Anderson notes that the academics have tended to drift off into irrelevant, often excessively abstract research while the engineers have lost contact with the source of ideas in the field. Neuroscience, he points out, provides a rich and valuable source of ideas about data representation and setting up the data representation is the major part of neural network programming. Both cognitive science and neuroscience give insights into how this can be done effectively: cognitive science suggests what to compute and neuroscience suggests how to compute it.

Author : Russell Beale,Tom Jackson
Publisher : Unknown
Page : 240 pages
File Size : 47,8 Mb
Release : 1994
Category : Electronic
ISBN : OCLC:604529721

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Neural Computing by Russell Beale,Tom Jackson Pdf

Author : Raul Rojas
Publisher : Springer Science & Business Media
Page : 511 pages
File Size : 47,6 Mb
Release : 2013-06-29
Category : Computers
ISBN : 9783642610684

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Neural Networks by Raul Rojas Pdf

Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.

Author : Kevin L. Priddy,Paul E. Keller
Publisher : SPIE Press
Page : 184 pages
File Size : 44,7 Mb
Release : 2005
Category : Computers
ISBN : 0819459879

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Artificial Neural Networks by Kevin L. Priddy,Paul E. Keller Pdf

This tutorial text provides the reader with an understanding of artificial neural networks (ANNs), and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed, and the data collection processes, to the many ways ANNs are being used today. The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach the engineer the guiding principles necessary to use and apply artificial neural networks.

Author : Igor Aleksander,Helen Morton
Publisher : Unknown
Page : 322 pages
File Size : 54,7 Mb
Release : 1995
Category : Computers
ISBN : UOM:39015034899974

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An Introduction to Neural Computing by Igor Aleksander,Helen Morton Pdf

The second edition of this text has been updated and includes material on new developments including neurocontrol, pattern analysis and dynamic systems. The book should be useful for undergraduate students of neural networks.

Author : Kevin Gurney
Publisher : CRC Press
Page : 234 pages
File Size : 42,5 Mb
Release : 2018-10-08
Category : Computers
ISBN : 9781482286991

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An Introduction to Neural Networks by Kevin Gurney Pdf

Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.

Author : Philip D. Wasserman
Publisher : Van Nostrand Reinhold Company
Page : 280 pages
File Size : 54,7 Mb
Release : 1993
Category : Computers
ISBN : UOM:39015029904201

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Advanced Methods in Neural Computing by Philip D. Wasserman Pdf

This is the engineer's guide to artificial neural networks, the advanced computing innovation which is posed to sweep into the world of business and industry. The author presents the basic principles and advanced concepts by means of high-performance paradigms which function effectively in real-world situations.

Author : Sankar Kumar Pal,Lech Polkowski
Publisher : Springer Science & Business Media
Page : 741 pages
File Size : 40,5 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642188596

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Rough-Neural Computing by Sankar Kumar Pal,Lech Polkowski Pdf

Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g. in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, genetic algorithms, and others. It is well understood now in the soft computing community that hybrid approaches combining various paradigms are very promising approaches for solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neuro computing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

Author : Berndt Müller,Joachim Reinhardt,Michael T. Strickland
Publisher : Springer Science & Business Media
Page : 340 pages
File Size : 41,9 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642577604

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Neural Networks by Berndt Müller,Joachim Reinhardt,Michael T. Strickland Pdf

Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.

Author : Igor Aleksander
Publisher : Van Nostrand Reinhold Company
Page : 240 pages
File Size : 44,6 Mb
Release : 1990-07-01
Category : Electronic
ISBN : 0442312180

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Intro to Neutral Computing by Igor Aleksander Pdf

Author : Igor Aleksander,Helen Morton
Publisher : Van Nostrand Reinhold Company
Page : 276 pages
File Size : 42,5 Mb
Release : 1990
Category : Computers
ISBN : UOM:39015019643264

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An Introduction to Neural Computing by Igor Aleksander,Helen Morton Pdf

The second edition of this text has been updated and includes material on new developments including neurocontrol, pattern analysis and dynamic systems. The book should be useful for undergraduate students of neural networks.

Author : Gustavo Deco,Dragan Obradovic
Publisher : Springer Science & Business Media
Page : 265 pages
File Size : 54,7 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461240167

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An Information-Theoretic Approach to Neural Computing by Gustavo Deco,Dragan Obradovic Pdf

A detailed formulation of neural networks from the information-theoretic viewpoint. The authors show how this perspective provides new insights into the design theory of neural networks. In particular they demonstrate how these methods may be applied to the topics of supervised and unsupervised learning, including feature extraction, linear and non-linear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural networks, but all the relevant concepts from information theory are carefully introduced and explained. Consequently, readers from varied scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this an extremely valuable introduction to this topic.

Author : Christopher M. Bishop
Publisher : Oxford University Press
Page : 501 pages
File Size : 43,8 Mb
Release : 1995-11-23
Category : Computers
ISBN : 9780198538646

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Neural Networks for Pattern Recognition by Christopher M. Bishop Pdf

Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.