Analogue Imprecision In Mlp Training, Progress In Neural Processing, Vol 4

Hardware inaccuracy and imprecision are important considerations when implementing neural algorithms. This book presents a study of synaptic weight noise as a typical fault model for analogue VLSI realisations of MLP neural networks and examines the implications for learning and network performance. The aim of the book is to present a study of how including an imprecision model into a learning scheme as a"fault tolerance hint" can aid understanding of accuracy and precision requirements for a particular implementation. In addition the study shows how such a scheme can give rise to significant performance enhancement.

Product details

• Authors: Peter Edwards, Peter J. Edwards, A.F. Murray, Alan F Murray, Alan F. Murray
• Publisher: World Scientific Publishing Company
• Languages: English
• Product format: Hardback
• Released: 01.08.1996
• EAN: 9789810227395
• ISBN: 978-981-02-2739-5
• No. of pages: 192
• Series: Progress in Neural Processing; Progress In Neural Processing
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > Data communication, networks