Adaptive fault tolerance for reliable LMS adaptive filtering

Bernard A. Schnaufer; W. Kenneth Jenkins

doi:10.1109/82.644560

Adaptive fault tolerance for reliable LMS adaptive filtering

Bernard A. Schnaufer, W. Kenneth Jenkins

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

Adaptive fault tolerance (AFT) is introduced and applied to finite impulse response (FIR) adaptive filters. Faulttolerant adaptive filters (FTAF's) that result from using the principles of AFT are analyzed with respect to convergence rate, computational complexity, and hardware overhead. A practical and useful FTAF based on the discrete Fourier transform (DFT) is developed that can tolerate numerous coefficient failures regardless of the input noise statistics. The aims of this paper are to demonstrate the principles of the AFT approach and to motivate future research in this area by drawing attention to similarities between AFT and other methods of fault tolerance that exploit adaptivity, such as neural networks.

Original language	English (US)
Pages (from-to)	1001-1014
Number of pages	14
Journal	IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing
Volume	44
Issue number	12
DOIs	https://doi.org/10.1109/82.644560
State	Published - 1997

All Science Journal Classification (ASJC) codes

Signal Processing
Electrical and Electronic Engineering

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10.1109/82.644560

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title = "Adaptive fault tolerance for reliable LMS adaptive filtering",

abstract = "Adaptive fault tolerance (AFT) is introduced and applied to finite impulse response (FIR) adaptive filters. Faulttolerant adaptive filters (FTAF's) that result from using the principles of AFT are analyzed with respect to convergence rate, computational complexity, and hardware overhead. A practical and useful FTAF based on the discrete Fourier transform (DFT) is developed that can tolerate numerous coefficient failures regardless of the input noise statistics. The aims of this paper are to demonstrate the principles of the AFT approach and to motivate future research in this area by drawing attention to similarities between AFT and other methods of fault tolerance that exploit adaptivity, such as neural networks.",

author = "Schnaufer, {Bernard A.} and Jenkins, {W. Kenneth}",

note = "Funding Information: Manuscript received June 2, 1995; revised April 17, 1997. This work was supported by the Joint Services Electronics Program (JSEP) at the University of Illinois under Grant N00014-96-1-0129. B. A. Schnaufer is with Rockwell Collins Avionics, Cedar Rapids, IA 52498 USA. W. K. Jenkins is with the Department of Electrical and Computer Engineering and Coordinated Science Laboratory, University of Illinois, Urbana, IL 61801 USA. Publisher Item Identifier S 1057-7130(97)07675-1.",

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AU - Jenkins, W. Kenneth

N1 - Funding Information: Manuscript received June 2, 1995; revised April 17, 1997. This work was supported by the Joint Services Electronics Program (JSEP) at the University of Illinois under Grant N00014-96-1-0129. B. A. Schnaufer is with Rockwell Collins Avionics, Cedar Rapids, IA 52498 USA. W. K. Jenkins is with the Department of Electrical and Computer Engineering and Coordinated Science Laboratory, University of Illinois, Urbana, IL 61801 USA. Publisher Item Identifier S 1057-7130(97)07675-1.

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N2 - Adaptive fault tolerance (AFT) is introduced and applied to finite impulse response (FIR) adaptive filters. Faulttolerant adaptive filters (FTAF's) that result from using the principles of AFT are analyzed with respect to convergence rate, computational complexity, and hardware overhead. A practical and useful FTAF based on the discrete Fourier transform (DFT) is developed that can tolerate numerous coefficient failures regardless of the input noise statistics. The aims of this paper are to demonstrate the principles of the AFT approach and to motivate future research in this area by drawing attention to similarities between AFT and other methods of fault tolerance that exploit adaptivity, such as neural networks.

AB - Adaptive fault tolerance (AFT) is introduced and applied to finite impulse response (FIR) adaptive filters. Faulttolerant adaptive filters (FTAF's) that result from using the principles of AFT are analyzed with respect to convergence rate, computational complexity, and hardware overhead. A practical and useful FTAF based on the discrete Fourier transform (DFT) is developed that can tolerate numerous coefficient failures regardless of the input noise statistics. The aims of this paper are to demonstrate the principles of the AFT approach and to motivate future research in this area by drawing attention to similarities between AFT and other methods of fault tolerance that exploit adaptivity, such as neural networks.

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Adaptive fault tolerance for reliable LMS adaptive filtering

Abstract

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