ANALOGUE IMPRECISION IN MLP TRAINING, PROGRESS IN NEURAL PROCESSING, VOL 4 by P J Edwards
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 afault 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.-
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| SKU | Unavailable |
| ISBN 13 | 9789810227395 |
| ISBN 10 | 9810227396 |
| Title | ANALOGUE IMPRECISION IN MLP TRAINING, PROGRESS IN NEURAL PROCESSING, VOL 4 |
| Author | Peter Edwards |
| Series | Progress In Neural Processing |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | World Scientific Publishing Co Pte Ltd |
| Year published | 1996-08-01 |
| Number of pages | 192 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |