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Improving Stochastic Computing Fault-Tolerance: A Case Study on Discrete Wavelet Transform

Document Type : Research article

Authors

Reliable and Smart Systems Lab (RSS), Shahid Bahonar University of Kerman, Kerman, Iran

Abstract

The stochastic computing (SC) method is a low-cost alternative to conventional binary computing that processes digital data in the form of pseudo-random bit-streams in which bit-flip errors have a trivial effect on the signal final value because of the highly redundant encoding format of this method. As a result, this computational method is used for fault-tolerant digital applications. In this paper, stochastic computing has been chosen to implement 2-dimensional discrete wavelet transform (2-D DWT) as a case study. The performance of the circuit is analyzed through two different faulty experiments. The results show that stochastic 2-D DWT outperforms binary implementation. Although SC provides inherent fault tolerance, we have proposed four structures based on dual modular redundancy to improve SC reliability. Improving the reliability of the stochastic circuits with the least area overhead is considered the main objective in these structures. The proposed methods are applied to improve the reliability of stochastic wavelet transform circuits. Experimental results show that all proposed structures improve the reliability of stochastic circuits, especially in extremely noisy conditions where fault tolerance of SC is reduced.

Highlights

  • Implementation of 2- dimensional discrete wavelet transform based on stochastic computing
  • Multiplexer-based error correction method in stochastic computing
  • C-element-based error correction method in stochastic computing
  • Error correction method based on repeating the operation for faulty bits to improve the stochastic computing fault tolerance
  • Error correction method based on the stochastic value of the signal to improve the stochastic computing fault tolerance

Keywords

Main Subjects

References
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Journal of Applied Research in Electrical Engineering
Volume 2, Issue 1
Winter and Spring 2023
January 2023
Pages 11-18
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History
  • Receive Date: 28 September 2021
  • Revise Date: 19 January 2022
  • Accept Date: 25 February 2022
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