Neural Network Applications: Proceedings of the Second British Neural Network Society Meeting (NCM91), London, October 1991 (Perspectives in Neural Computing)

Taylor, J.G.

ISBN 10: 3540197729 / ISBN 13: 9783540197720

Published by Springer, 1992

About this Item

166 pages. 9.53x6.69x0.38 inches. In Stock.

Seller Inventory # x-3540197729

Bibliographic Details

• Title: Neural Network Applications: Proceedings of the Second British Neural Network Society Meeting (NCM91), London, October 1991 (Perspectives in Neural Computing)
• Publisher: Springer
• Publication Date: 1992
• Language: English
• ISBN 10: 3540197729
• ISBN 13: 9783540197720
• Binding: Paperback
• Condition: Brand New
• Weight: 0.3 kilograms

About this title

Synopsis

Neural Network Applications contains the 12 papers presented at the second British Neural Network Society Meeting (NCM '91) held at King's College London on 1st October 1991. The meeting was sponsored by the Centre for Neural Networks, King's College, and the British Neural Network Society, and was also part of the DEANNA ESPRIT programme. The papers reflect the wide spectrum of neural network applications that are currently being attempted in industry and medicine. They cover medical diagnosis, robotics, plant control, machine learning, and visual inspection, as well as more general discussions on net learning and knowledge representation. The breadth and depth of coverage is a sign of the health of the subject, as well as indicating the importance of neural network developments in industry and the manner in which the applications are progressing. Among the actual topics covered are: Learning algorithms - theory and practice; A review of medical diagnostic applications of neural networks; Simulated ultrasound tomographic imaging of defects; Linear quadtrees for neural network based position invariant pattern recognition; The pRTAM as a hardware-realisable neuron; The cognitive modalities ("CM") system of knowledge representation - the DNA of neural networks? This volume provides valuable reading for all those attempting to apply neural networks, as well as those entering the field, including researchers and postgraduate students in computational neuroscience, neurobiology, electrical engineering, computer science, mathematics, and medicine.