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Convergence Property of Conjugate Gradient Algorithm and Its Fast Tracking Algorithm
Dai Il KIM
Philippe De WILDE
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2000/11/25
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Digital Signal Processing
conjugate gradient algorithm, steepest descent,
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This article addresses two issues. Firstly, the convergence property of conjugate gradient (CG) algorithm is investigated by a Chebyshev polynomial approximation. The analysis result shows that its convergence behaviour is affected by an acceleration term over the steepest descent (SD) algorithm. Secondly, a new CG algorithm is proposed in order to boost the tracking capability for time-varying parameters. The proposed algorithm based on re-initialising forgetting factor shows a fast tracking ability and a noise-immunity property when it encounters an unexpected parameter change. A fast tracking capability is verified through a computer simulation in a system identification problem.