Low power adaptive filters based on a combination of Genetic optimization and residue number system coding

C. Radhakrishnan, William Kenneth Jenkins, D. J. Krusienski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper investigates design strategies for achieving reliable performance in low power VLSI adaptive filters that are prone to transient errors due to increasingly smaller feature dimensions and supply voltages of the CMOS circuits. First it is shown that a well known stochastic search algorithm, the Genetic Algorithm, has an inherent resistance to transient (soft) errors that may occur due to feature scaling. It is then shown how modular hardware can be designed with residue number system (RNS) coding to provide improved resistance to transient (soft) errors in low power realizations of adaptive filters that optimize the filter parameters via the Genetic Algorithm.

Original languageEnglish (US)
Title of host publicationConference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC
Pages1417-1421
Number of pages5
DOIs
StatePublished - Dec 1 2007
Event41st Asilomar Conference on Signals, Systems and Computers, ACSSC - Pacific Grove, CA, United States
Duration: Nov 4 2007Nov 7 2007

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other41st Asilomar Conference on Signals, Systems and Computers, ACSSC
CountryUnited States
CityPacific Grove, CA
Period11/4/0711/7/07

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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