A New Stochastic Inner Product Core Design for Digital FIR Filters

Ming Ming Wong, M. L. Dennis Wong, Cishen Zhang, Ismat Hijazin

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Stochastic computing (SC) is a computational technique with computational operations governed by probability instead of arithmetic rules. It recently found promising applications in digital and image processing areas and attracted attentions of researchers. In this paper, a new stochastic inner product (multiply and accumulate) core with an improved scaling scheme is presented for improving the accuracy and fault tolerance performance of SC based finite impulse response (FIR) digital filters. The proposed inner product core is designed using tree structured multiplexers which is capable of reducing the critical path and fault propagation in the stochastic circuitry. The designed inner product core can lead to construction of SC based light weight and multiplierless FIR digital filters. As a result, an SC based FIR digital FIR filter is implemented on Altera Cyclone V FPGA which operates on stochastic sequences of 256-bits length (8-bits precision level). Experimental results show that the developed filter has lower hardware cost, better accuracy and higher fault tolerance level compared with other stochastic implementations.
Original languageEnglish
Article number05006
Number of pages5
JournalMATEC Web of Conferences
Publication statusPublished - 4 Oct 2017

ASJC Scopus subject areas

  • Signal Processing


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