FFT-based RLS in signal processing

Authors:
Robert J. Plemmons
Affiliations:
Computer Science Dept., Wake Forest University, Winston-Salem, NC
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: digital speech processing - Volume III
Year:
1993

Citing 5
Cited 0

A proposal for toeplitz matrix calculations

Studies in Applied Mathematics
Discrete-time signal processing

Discrete-time signal processing
Adaptive filter theory (2nd ed.)

Adaptive filter theory (2nd ed.)
FFT-based preconditioners for Toeplitz-block least squares problems

SIAM Journal on Numerical Analysis
Circulant Preconditioned Toeplitz Least Squares Iterations

SIAM Journal on Matrix Analysis and Applications

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Abstract

This paper proposes a new algorithm for fast adaptiue filtering. The algorithm applies an FFT-based iterative method and uses sliding data windows inuoluing block updating and downdating computations. The method is stable and robust, and computes the tap weight filter vector in O(L log N) operations, where the sliding window Toeplitz data matrix X is L-by-N. The complexity thus generally lies between those of the family of unstable but fast, O(N), methods and the stable but slow, O(N2), Cholesky factor updating methods.