A New Adaptive Convergence Factor Algorithm with the Constant Damping Parameter
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概要
- 論文の詳細を見る
This paper presents a new Adaptive Convergence Factor (ACF) algorithm without the damping parameter adjustment according 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 timevariable systems and the system identification. 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.
- 社団法人電子情報通信学会の論文
- 1995-06-25
著者
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Fukui Yutaka
Faculty Of Engineering Setsunan University
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Nakanishi Isao
Faculty Of Education Tottori University
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Fukui Yutaka
Faculty Of Engineering Tottori University
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