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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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .




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 sucess 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. The Promise of Neural Networksprovides 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 theiravailable hardware and software simulators. The second part discusses deeper principles, and reviews a range of applications. The final part describes the results of the DEANNA questionnaire, and provides a summary of developmentsin current European neural network activity.


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 sucess 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. The Promise of Neural Networksprovides 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 theiravailable hardware and software simulators. The second part discusses deeper principles, and reviews a range of applications. The final part describes the results of the DEANNA questionnaire, and provides a summary of developmentsin current European neural network activity.
Content:
Front Matter....Pages i-viii
Front Matter....Pages 1-1
Deanna....Pages 3-7
Neural Net Demonstrators....Pages 9-23
Neural Net Simulators....Pages 25-33
Front Matter....Pages 35-35
Introduction to Neural Computing....Pages 37-72
The Principles of Neural Networks....Pages 73-84
Applications of Neural Networks....Pages 85-95
Front Matter....Pages 97-97
The DEANNA Database....Pages 99-121
Whither Neural Networks?....Pages 123-155
Back Matter....Pages 157-160


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 sucess 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. The Promise of Neural Networksprovides 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 theiravailable hardware and software simulators. The second part discusses deeper principles, and reviews a range of applications. The final part describes the results of the DEANNA questionnaire, and provides a summary of developmentsin current European neural network activity.
Content:
Front Matter....Pages i-viii
Front Matter....Pages 1-1
Deanna....Pages 3-7
Neural Net Demonstrators....Pages 9-23
Neural Net Simulators....Pages 25-33
Front Matter....Pages 35-35
Introduction to Neural Computing....Pages 37-72
The Principles of Neural Networks....Pages 73-84
Applications of Neural Networks....Pages 85-95
Front Matter....Pages 97-97
The DEANNA Database....Pages 99-121
Whither Neural Networks?....Pages 123-155
Back Matter....Pages 157-160
....
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