NDLI: Block adaptive IIR filters using preconditioned conjugate gradients for orthogonalization

Content Provider	IEEE Xplore Digital Library
Author	Hull, A.W. Jenkins, W.K.
Copyright Year	1995
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA (Hull, A.W.)
Abstract	The method of preconditioned conjugate gradients (PCG) is introduced as an accelerator for simple IIR algorithms to significantly increase their rate of convergence without dramatically adding to their complexity. This paper develops a block Newton-type adaptive IIR digital filter with complexity O(log(N)). The proposed algorithm exploits a structured approximation to the Hessian which permits the application of a fast preconditioned conjugate gradient optimization method. In this novel formulation, the identification problem of the IIR coefficients separates into two subproblems, each of which may be solved by application of fast adaptive FIR techniques. Present IIR algorithms require greater computational cost, or converge more slowly. It is the adoption of fast PCG which permits the development of an O(log(N)) adaptive algorithm. The PCG method manipulates an approximation of the Hessian matrix to form an orthogonalizing update term for the IIR LMS algorithm. Rapid convergence follows, and the method is robust with respect to fixed-point instability. The use of preconditioned conjugate gradients in the Gauss-Newton update leads naturally to the application of the planar least squares inverse to bound the poles of the adaptive system by projecting an unstable denominator onto a stable polynomial. This technique is invoked whenever the output of the adaptive filter exceeds a certain threshold. This approach provides a computationally efficient means to ensure robust IIR adaptive behavior.
Starting Page	1384
Ending Page	1387
File Size	428528
Page Count	4
File Format	PDF
ISBN	0780324315
ISSN	15206149
DOI	10.1109/ICASSP.1995.480499
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-05-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	IIR filters Least squares approximation Convergence Approximation algorithms Robustness Least squares methods Digital filters Optimization methods Finite impulse response filter Computational efficiency
Content Type	Text
Resource Type	Article

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