Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89118
Title: Stochastic inner product core for digital FIR filters
Authors: Hijazin, Ismat
Wong, Ming Ming
Wong, Dennis
Zhang, Cishen
Keywords: DRNTU::Engineering::Computer science and engineering
Inner Product
Stochastic Computing
Issue Date: 2017
Source: Wong, M. M., Wong, D., Zhang, C., & Hijazin, I. (2017). Stochastic inner product core for digital FIR filters. WSEAS Transactions on Systems and Control, 12, 246-252.
Series/Report no.: WSEAS Transactions on Systems and Control
Abstract: The computational operations of stochastic computing (SC) are governed by probability rules which is different from conventional arithmetic computations. Applications of SC to digital signal and image processing problems have been recently reported in the literature. To improve the computational performance of SC based finite impulse response (FIR) digital filters, 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 the filters. Taking into account the symmetric property of the coefficients of linear phase FIR 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.
URI: https://hdl.handle.net/10356/89118
http://hdl.handle.net/10220/46080
ISSN: 1991-8763
Rights: © 2017 The Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0
metadata.item.grantfulltext: open
metadata.item.fulltext: With Fulltext
Appears in Collections:SCSE Journal Articles

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