The Promise of Neural Networks (Paperback)

J.G. Taylor

ISBN 10: 3540197737 / ISBN 13: 9783540197737

Editore: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 1993

Riguardo questo articolo

Paperback. The neural network is one of the most exciting new tools for information processing to have emerged over the last few years. An increasing number of computer tasks require the use of human-like capabilities, a fact which has caused severe problems for many industries and services in the past. Now, however, neural networks are being developed which can handle a broad range of tasks in vision, speed recognition, time series analysis, robotics and control. They have proved particularly useful in dealing with problems which cannot be solved by explicit rules, which involve noisy data, and which allow a system to be trained by examples. In response to increasing neural network activity during the 1980s, the DEANNA Project (Database for European Artificial Neural Network Activity) was established in 1990 (ESPRIT Project P5668). The main objective of this 15-month EC-funded project was to construct a database of current European neural computing research which could be used to assess the success of various applications, and to pinpoint the major difficulties in technology transfer.The project also aimed to create a European neural network advisory structure, and to develop neural computing simulators and demonstrators. This text contains a comprehensive overview of neural networks based on the findings of the DEANNA Project, together with a view of the broader framework of the subject in a world context. The first part of the report describes neural nets and their available hardware and software simulators. The second part discusses deeper principles, and reviews a range of applications. The final section describes the results of the DEANNA questionnaire, and provides a summary of developments in current European neural network activity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1 . 3 . 6 1 . 4 The Plan for Neural Networks . 1 The Status of Neural Networks . 2 Reasons for the Employment of Neural Networks . 3 Neural Network Models . 4 Areas of Application . 5 Typical Applications . Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Codice articolo 9783540197737

Dati bibliografici

• Titolo: The Promise of Neural Networks (Paperback)
• Editore: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin
• Data di pubblicazione: 1993
• Lingua: Inglese
• ISBN 10: 3540197737
• ISBN 13: 9783540197737
• Rilegatura: Paperback
• Condizione: new

Descrizione articolo

Riassunto

This book is the product of a 15-month intensive investigation of the European artificial network scene, together with a view of the broader framework of the subject in a world context. It could not have been completed in such a remarkably short time, and so effectively, without the dedicated efforts of Louise Turner, the DEANNA secretary, and Geoff Chappell, the DEANNA researcher, at the Centre for Neural Networks, King's College, London. I would like to take this opportunity to thank them for their heroic efforts. I would also like to thank my colleagues in the Centre and in the Mathematics Department, especially Mark Plumbley, Michael Reiss and Trevor Clarkson for all their help and encouragement, Denise Gorse of University College London, for allowing use of her lecture notes as a basis for the tutorial and the DEANNA partners for the part they played. Finally I would like to acknowledge the European Community support, and especially Mike Coyle for his trenchant comments during the carrying out of the work. March 1993 J. G. Taylor CONTENTS PART I: SETTING THE SCENE Chapter 1: DEANNA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1 . 1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 . 2 The Geographical Dimension. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1 1. 3 The Industrial Dimension. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1 . 4 The Plan for Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Chapter 2: Neural Net Demonstrators. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2. 1 The Status of Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2. 2 Reasons for the Employment of Neural Networks . . . . . . . . . . . . . . . . . . . 9 2. 3 Neural Network Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2. 4 Areas of Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2. 5 Typical Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Contenuti

I: Setting the Scene.- 1: DEANNA.- 1.1 Introduction.- 1.2 The Geographical Dimension.- 1.3 The Industrial Dimension.- 1.4 The Plan for Neural Networks.- 2: Neural Net Demonstrators.- 2.1 The Status of Neural Networks.- 2.2 Reasons for the Employment of Neural Networks.- 2.3 Neural Network Models.- 2.4 Areas of Application.- 2.5 Typical Applications.- 2.6 Devices for Running Neural Nets.- 2.7 Applications References.- 3: Neural Net Simulators.- 3.1 Software Simulators.- 3.2 Hardware Simulators.- 3.3 Neural Network Chips.- II: Neural Networks Proper.- 4: Introduction to Neural Computing.- 4.1 History of Neurocomputing.- 4.2 Artificial Neural Networks (ANNs).- 4.3 The Biological Prototype.- 4.4 Types of Neural Nets.- 4.5 Learning Nets.- 4.6 Perceptron Learning.- 4.7 Limitations of Perceptrons.- 4.8 Backpropagation.- 4.9 Visualising Network Behaviour: the Error Weight Surface.- 4.10 The Hopfield Network.- 4.11 Topographic Maps.- 4.12 Reinforcement Training.- 4.13 Further Reading.- 4.14 Appendix.- 5: The Principles of Neural Networks.- 5.1 The Problem of Principles.- 5.2 Mathematical Approaches.- 5.3 Informational Approaches.- 5.4 Psychological Approaches.- 5.5 Logical Approaches.- 5.6 Genetic Approaches.- 5.7 References.- 6: Applications of Neural Networks.- 6.1 Introduction.- 6.2 Speech Recognition.- 6.3 Pattern Recognition.- 6.4 Medical Applications of Neural Networks.- 6.5 Control.- 6.6 Time Series.- 6.7 References.- III: The Future of Neural Networks.- 7: The DEANNA Database.- 7.1 The Questionnaire.- 7.2 Starting Up.- 7.3 Algorithms.- 7.4 Applications.- 7.5 Comments.- 7.6 References.- 7.7 Appendixes.- Appendix 1 The DEANNA Survey.- Appendix 2 DEANNA at ICANN ‘81.- 8: Whither Neural Networks?.- 8.1 Future Developments.- 8.2 Future Applications.- 8.3 Advisory Structure.- 8.4 The Future of Neural Networks.- 8.5 References.- 8.6 Appendixes.- Appendix 1 Large (8 or more) European Neural Network Groups.- Appendix 2 Networks of Excellence Proposal.- Appendix 3 Network Proposal on Theory of Neural Networks.- Glossary of Neural Network Terms.