ANALOGUE IMPRECISION IN MLP TRAINING, PROGRESS IN NEURAL PROCESSING, VOL 4 (Progress in Neural Processing, 4),Used

ANALOGUE IMPRECISION IN MLP TRAINING, PROGRESS IN NEURAL PROCESSING, VOL 4 (Progress in Neural Processing, 4),Used

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SKU: SONG9810227396
Brand: World Scientific Publishing Company
Condition: Used
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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.

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