Abstract
An approach for designing multiplierless multilayer feedforward neural networks using quantised neurons is proposed. The design has significant merits for digital VLSI implementation in terms of reduced silicon area and increased operational speed. As compared to one-powers-of-two weights approaches of multiplierless design, the quantised neurons approach offers additional advantages of simplicity in activation function realisation and freedom in weights adaptation.
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