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Analogue Imprecision In Mlp Training, Progress In Neural Processing, Vol 4 (Progress In Neural Processing 4)
By: A.F. Murray (author), Peter J. Edwards (author)HardbackUp to 2 WeeksUsually despatched within 2 weeks
Description
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.Contents
Neural network performance metrics; noise in neural implementations; simulation requirements and environment; fault tolerance; generalisation ability; learning trajectory and speed.Product Details
- publication date: 01/08/1996
- ISBN13: 9789810227395
- Format: Hardback
- Number Of Pages: 192
- ID: 9789810227395
- ISBN10: 9810227396
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- Saver Delivery: Yes
- 1st Class Delivery: Yes
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