An Introduction To Neural Networks

An Introduction To Neural Networks by James A. Anderson. Download it An Introduction To Neural Networks books also available in PDF, EPUB, and Mobi Format for read it on your Kindle device, PC, phones or tablets. 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 .... Click Download for free books.

An Introduction To Neural Networks

An Introduction To Neural Networks
Author: James A. Anderson
Publisher: MIT Press
ISBN: 9780262510813
Size: 14.71 MB
Format: PDF, ePub
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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.
An Introduction to Neural Networks
Language: en
Pages: 234
Authors: Kevin Gurney
Categories: Computers
Type: BOOK - Published: 2018-10-08 - Publisher: CRC Press
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
An Introduction to Neural Networks
Language: en
Pages: 650
Authors: James A. Anderson
Categories: Computers
Type: BOOK - Published: 1995 - Publisher: MIT Press
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
Introduction to Neural Networks with Java
Language: en
Pages: 440
Authors: Jeff Heaton
Categories: Computers
Type: BOOK - Published: 2008 - Publisher: Heaton Research, Inc.
Introduction to Neural Networks in Java, Second Edition, introduces the Java programmer to the world of Neural Networks and Artificial Intelligence. Neural network architectures such as the feedforward, Hopfield, and Self Organizing Map networks are discussed. Training techniques such as Backpropagation, Genetic Algorithms and Simulated Annealing are also introduced. Practical
An Introduction to Biological and Artificial Neural Networks for Pattern Recognition
Language: en
Pages: 220
Authors: Steven K. Rogers, Matthew Kabrisky
Categories: Computers
Type: BOOK - Published: 1991 - Publisher: SPIE Press
Books about An Introduction to Biological and Artificial Neural Networks for Pattern Recognition
An Introduction to Neural Computing
Language: en
Pages: 284
Authors: Igor Aleksander, Helen Morton
Categories: Computers
Type: BOOK - Published: 1995 - Publisher: Itp - Media
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.
Artificial Neural Networks
Language: en
Pages: 293
Authors: P.J. Braspenning, F. Thuijsman, A.J.M.M. Weijters
Categories: Computers
Type: BOOK - Published: 1995-06-02 - Publisher: Springer Science & Business Media
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
An Introduction to Neural Networks
Language: en
Pages: 135
Authors: Ben Kröse, Patrick van der Smagt
Categories: Neural networks (Computer science)
Type: BOOK - Published: 1996 - Publisher:
Books about An Introduction to Neural Networks
Artificial Neural Networks
Language: en
Pages: 165
Authors: Kevin L. Priddy, Paul E. Keller
Categories: Technology & Engineering
Type: BOOK - Published: 2005 - Publisher: SPIE Press
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
An Introduction to Neural Network Methods for Differential Equations
Language: en
Pages: 114
Authors: Neha Yadav, Anupam Yadav, Manoj Kumar
Categories: Mathematics
Type: BOOK - Published: 2015-02-26 - Publisher: Springer
This book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand
Introduction to Neural Networks
Language: en
Pages: 168
Authors: P. D. Picton
Categories: Artificial intelligence
Type: BOOK - Published: 1994-11-11 - Publisher: Macmillan International Higher Education
This book introduces neural networks. It describes what they are, what they can do and how they do it. While some scientific background is assumed, the reader is not expected to have any prior knowledge of neural networks. These networks are explained and discussed by means of examples, so that