Novel LMS algorithms based on status categorization
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概要
- 論文の詳細を見る
Least Mean Square (LMS) is an effective adaptive filtering algorithm with advantages of robustness and simplicity. In this paper, we propose two new algorithms, Categorized Variable Step Size LMS (CVSSLMS) and Combined CVSSLMS (CCVSSLMS), based on the categorization of filter status. The step sizes of the proposed algorithms are dynamically updated by optimization for each state. Experiment results show that the proposed algorithms outperform conventional LMS algorithms in both simplicity and robustness.
- The Institute of Electronics, Information and Communication Engineersの論文
著者
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Lim Jun-seok
Department Of Electronics Engineering Sejong Univ.
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Chon Sang
Applied Acoustics Lab. School Of Electrical Eng. And Computer Science Seoul National University
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Sung Koeng-Mo
Applied Acoustics Lab., Institute of New Media and Communications, Department of Electrical Engineering, Seoul National University
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Sung Koeng-Mo
Applied Acoustics Laboratory, Institute of New Media and Communications, School of Electrical Engineering and Computer Science, Seoul National University
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Kim Seon-Ho
Applied Acoustics Laboratory, Institute of New Media and Communications, School of Electrical Engineering and Computer Science, Seoul National University
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Chon Sang
Applied Acoustics Laboratory, Institute of New Media and Communications, School of Electrical Engineering and Computer Science, Seoul National University
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