2000年
漸近的に最適はRLS適応同足アルゴリズム
システム制御情報学会論文誌
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- 巻
- 13
- 号
- 1
- 開始ページ
- 1
- 終了ページ
- 13
- 記述言語
- 日本語
- 掲載種別
- DOI
- 10.5687/iscie.13.1
- 出版者・発行元
- 一般社団法人 システム制御情報学会
A major, and yet unresolved, problem has been the choice of the gain adjusting parameter in some parameter estimation algorithms. This paper presents an adaptive setting method of the forgetting factor for estimating time-varying parameters when the Recursive Least Squares (RLS) algorithm is used. The method is to choose the forgetting factor λ so as to minimize the performance index defined by E {ε2t (λ)} where εt (λ) is the prediction error based on some λ. This is concretely done by solving the minimization problem of a certain object function with respect to λ. It is shown that this object function is unimodal with respect to λ and thus the minimization can be attained by using the stochastic Newton method. As a result, the proposed method becomes asymptotically optimal. The resultant algorithm can be executed by linking the minimization routine with RLS.<BR>Numerical examples indicate acceptable performance.
- リンク情報
- ID情報
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- DOI : 10.5687/iscie.13.1
- ISSN : 1342-5668
- CiNii Articles ID : 10004472683
- CiNii Books ID : AN1013280X