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

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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 f or 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.Format: HardcoverNo of Pages: 192Imprint: World ScientificPublication date: 19960801Series: Progress In Neural Processing Show more