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

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

doi:10.1109/ACSSC.2007.4487462

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 proceeding › Conference 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 language	English (US)
Title of host publication	Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC
Pages	1417-1421
Number of pages	5
DOIs	https://doi.org/10.1109/ACSSC.2007.4487462
State	Published - Dec 1 2007
Event	41st Asilomar Conference on Signals, Systems and Computers, ACSSC - Pacific Grove, CA, United States Duration: Nov 4 2007 → Nov 7 2007

Publication series

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

Other

Other	41st Asilomar Conference on Signals, Systems and Computers, ACSSC
Country/Territory	United States
City	Pacific Grove, CA
Period	11/4/07 → 11/7/07

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/ACSSC.2007.4487462

Cite this

Radhakrishnan, C., Jenkins, W. K., & Krusienski, D. J. (2007). Low power adaptive filters based on a combination of Genetic optimization and residue number system coding. In Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC (pp. 1417-1421). Article 4487462 (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2007.4487462

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

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.",

author = "C. Radhakrishnan and Jenkins, {William Kenneth} and Krusienski, {D. J.}",

year = "2007",

month = dec,

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doi = "10.1109/ACSSC.2007.4487462",

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isbn = "9781424421107",

series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

pages = "1417--1421",

booktitle = "Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC",

note = "41st Asilomar Conference on Signals, Systems and Computers, ACSSC ; Conference date: 04-11-2007 Through 07-11-2007",

}

Radhakrishnan, C, Jenkins, WK & Krusienski, DJ 2007, Low power adaptive filters based on a combination of Genetic optimization and residue number system coding. in Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC., 4487462, Conference Record - Asilomar Conference on Signals, Systems and Computers, pp. 1417-1421, 41st Asilomar Conference on Signals, Systems and Computers, ACSSC, Pacific Grove, CA, United States, 11/4/07. https://doi.org/10.1109/ACSSC.2007.4487462

Low power adaptive filters based on a combination of Genetic optimization and residue number system coding. / Radhakrishnan, C.; Jenkins, William Kenneth; Krusienski, D. J.
Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC. 2007. p. 1417-1421 4487462 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - 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.

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Radhakrishnan C, Jenkins WK, Krusienski DJ. Low power adaptive filters based on a combination of Genetic optimization and residue number system coding. In Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC. 2007. p. 1417-1421. 4487462. (Conference Record - Asilomar Conference on Signals, Systems and Computers). doi: 10.1109/ACSSC.2007.4487462

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

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