WSEAS Transactions on Systems and Control

Print ISSN: 1991-8763
E-ISSN: 2224-2856

Volume 12, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

Volume 12, 2017

Stochastic Inner Product Core for Digital FIR Filters

AUTHORS : Ming Ming Wong, Dennis Wong, Cishen Zhang, Ismat Hijazin

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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.

KEYWORDS : Stochastic computing, Inner product, Digital FIR filters


[1] B. R. Gaines,‘Stochastic computing’, Proceedings of the Spring Joint Computer Conference, New York, NY, USA, pp. 149-156,(1967).

[2] A. Alaghi, and J. P. Hayes,‘Survey of Stochastic Computing’, ACM Trans. Embed. Comput. Syst., vol. 12, no. 2, pp. 19, (2013), .

[3] W. Qian, X. Li, M. D. Riedel, K. Bazargan, and D. J. Lilja, ‘An architecture for fault-tolerant computation with stochastic logic’,IEEE Transactions on Computers, vol. 60, no. 1, pp. 93-105, (2011).

[4] B. Moons, and M. Verhelst, ‘Energy-efficiency and accuracy of stochastic computing circuits in emerging technologies’, IEEE Journal on E,merging and Selected Topics in Circuits and Systems, vol. 4, no. 4, pp. 475-486, (2014).

[5] Y. N. Chang, and K. K. Parhi, ‘Architectures for digital filters using stochastic computing’, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2697-2701, (2013).

[6] Y. Liu, and K. K. Parhi,‘Lattice fir digital filter architectures using stochastic computing’, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1027-1031, (2015).

WSEAS Transactions on Systems and Control, ISSN / E-ISSN: 1991-8763 / 2224-2856, Volume 12, 2017, Art. #26, pp. 246-252

Copyright © 2017 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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