A New Adaptive Convergence Factor Algorithm with the Constant Damping Parameter


IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E78-A   No.6   pp.649-655
Publication Date: 1995/06/25
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section of Papers Selected from 1994 Joint Technical Conference on Circuits/Systems, Computers and Communications (JTC-CSCC '94))
adaptive filter,  adaptive convergence factor algorithm,  damping parameter,  normalization,  

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This paper presents a new Adaptive Convergence Factor (ACF) algorithm without the damping parameter adjustment acoording to the input signal and/or the composition of the filter system. The damping parameter in the ACF algorithms has great influence on the convergence characteristics. In order to examine the relation between the damping parameter and the convergence characteristics, the normalization which is realized by the related signal terms divided by each maximum value is introduced into the ACF algorithm. The normalized algorithm is applied to the modeling of unknown time-variable systems which makes it possible to examine the relation between the parameters and the misadjustment in the adaptive algorithms. Considering the experimental and theoretical results, the optimum value of the damping parameter can be defined as the minimum value where the total misadjustment becomes minimum. To keep the damping parameter optimum in any conditions, the new ACF algorithm is proposed by improving the invariability of the damping parameter in the normalized algorithm. The algorithm is investigated by the computer simulations in the modeling of unknown time-variable systems and the system indentification. The results of simulations show that the proposed algorithm needs no adjustment of the optimum damping parameter and brings the stable convergence characteristics even if the filter system is changed.