Title :
Adaptive fault tolerance for reliable LMS adaptive filtering
Author :
Schnaufer, Bernard A. ; Jenkins, W. Kenneth
Author_Institution :
Rockwell Collins Avionics, Cedar Rapids, IA, USA
fDate :
12/1/1997 12:00:00 AM
Abstract :
Adaptive fault tolerance (AFT) is introduced and applied to finite impulse response (FIR) adaptive filters, Fault-tolerant adaptive filters (FTAFs) 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
Keywords :
FIR filters; adaptive filters; computational complexity; convergence of numerical methods; discrete Fourier transforms; filtering theory; least mean squares methods; reliability; DFT; FIR adaptive filters; adaptive fault tolerance; coefficient failures; computational complexity; convergence rate; discrete Fourier transform; fault-tolerant adaptive filters; finite impulse response; hardware overhead; reliable LMS adaptive filtering; Adaptive filters; Computational complexity; Convergence; Discrete Fourier transforms; Fault tolerance; Finite impulse response filter; Hardware; Least squares approximation; Neural networks; Statistics;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on