An Introduction To Neural Computing
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An Introduction To Neural Computing
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Author : Igor Aleksander
language : en
Publisher: Van Nostrand Reinhold Company
Release Date : 1990
An Introduction To Neural Computing written by Igor Aleksander and has been published by Van Nostrand Reinhold Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.
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.
An Introduction To Neural Networks
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Author : Kevin Gurney
language : en
Publisher: CRC Press
Release Date : 2018-10-08
An Introduction To Neural Networks written by Kevin Gurney and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-08 with Computers categories.
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.
Neural Computing An Introduction
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Author : R Beale
language : en
Publisher: CRC Press
Release Date : 1990-01-01
Neural Computing An Introduction written by R Beale and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-01-01 with Mathematics categories.
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.
An Introduction To Neural Networks
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Author : James A. Anderson
language : en
Publisher: MIT Press
Release Date : 1995
An Introduction To Neural Networks written by James A. Anderson and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
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.
Artificial Neural Networks
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Author : Kevin L. Priddy
language : en
Publisher: SPIE Press
Release Date : 2005
Artificial Neural Networks written by Kevin L. Priddy and has been published by SPIE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
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.
Introduction To The Theory Of Neural Computation
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Author : John A. Hertz
language : en
Publisher: CRC Press
Release Date : 2018-03-08
Introduction To The Theory Of Neural Computation written by John A. Hertz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-08 with Science categories.
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.
Artificial Neural Networks
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Author : P.J. Braspenning
language : en
Publisher: Springer Science & Business Media
Release Date : 1995-06-02
Artificial Neural Networks written by P.J. Braspenning and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-06-02 with Computers categories.
This book presents carefully revised versions of tutorial lectures given during a School on Artificial Neural Networks for the industrial world held at the University of Limburg in Maastricht, Belgium. The major ANN architectures are discussed to show their powerful possibilities for empirical data analysis, particularly in situations where other methods seem to fail. Theoretical insight is offered by examining the underlying mathematical principles in a detailed, yet clear and illuminating way. Practical experience is provided by discussing several real-world applications in such areas as control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM.
Neural Networks
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Author : Raul Rojas
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Neural Networks written by Raul Rojas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Computers categories.
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.
Neural Networks In Bioprocessing And Chemical Engineering
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Author : D. R. Baughman
language : en
Publisher: Academic Press
Release Date : 2014-06-28
Neural Networks In Bioprocessing And Chemical Engineering written by D. R. Baughman and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Science categories.
Neural networks have received a great deal of attention among scientists and engineers. In chemical engineering, neural computing has moved from pioneering projects toward mainstream industrial applications. This book introduces the fundamental principles of neural computing, and is the first to focus on its practical applications in bioprocessing and chemical engineering. Examples, problems, and 10 detailed case studies demonstrate how to develop, train, and apply neural networks. A disk containing input data files for all illustrative examples, case studies, and practice problems provides the opportunity for hands-on experience. An important goal of the book is to help the student or practitioner learn and implement neural networks quickly and inexpensively using commercially available, PC-based software tools. Detailed network specifications and training procedures are included for all neural network examples discussed in the book.Each chapter contains an introduction, chapter summary, references to further reading, practice problems, and a section on nomenclatureIncludes a PC-compatible disk containing input data files for examples, case studies, and practice problemsPresents 10 detailed case studiesContains an extensive glossary, explaining terminology used in neural network applications in science and engineeringProvides examples, problems, and ten detailed case studies of neural computing applications, including:Process fault-diagnosis of a chemical reactorLeonardKramer fault-classification problemProcess fault-diagnosis for an unsteady-state continuous stirred-tank reactor systemClassification of protein secondary-structure categoriesQuantitative prediction and regression analysis of complex chemical kineticsSoftware-based sensors for quantitative predictions of product compositions from flourescent spectra in bioprocessingQuality control and optimization of an autoclave curing process for manufacturing composite materialsPredictive modeling of an experimental batch fermentation processSupervisory control of the Tennessee Eastman plantwide control problemPredictive modeling and optimal design of extractive bioseparation in aqueous two-phase systems