A Variable Step-Size Proportionate NLMS Algorithm for Identification of Sparse Impulse Response
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概要
- 論文の詳細を見る
Recently, proportionate adaptive algorithms have been proposed to speed up convergence in the identification of sparse impulse response. Although they can improve convergence for sparse impulse responses, the steady-state misalignment is limited by the constant step-size parameter. In this article, based on the principle of least perturbation, we first present a derivation of normalized version of proportionate algorithms. Then by taking the disturbance signal into account, we propose a variable step-size proportionate NLMS algorithm to combine the benefits of both variable step-size algorithms and proportionate algorithms. The proposed approach can achieve fast convergence with a large step size when the identification error is large, and then considerably decrease the steady-state misalignment with a small step size after the adaptive filter reaches a certain degree of convergence. Simulation results verify the effectiveness of the proposed approach.
- （社）電子情報通信学会の論文
- 2010-01-01
著者
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FUKUMOTO Masahiro
Department of Production Systems Engineering, Toyohashi University of Technology
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Fukumoto Masahiro
Department Of Information Systems Engineering Kochi University Of Technology
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LIU Ligang
Department of Information Systems Engineering, Kochi University of Technology
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SAIKI Sachio
Department of Information Systems Engineering, Kochi University of Technology
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ZHANG Shiyong
School of Computer Science and Technology, Fudan University
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Liu Ligang
Department Of Information Systems Engineering Kochi University Of Technology
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Saiki Sachio
Department Of Information Systems Engineering Kochi University Of Technology
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Zhang Shiyong
School Of Computer Science And Technology Fudan University
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- PREFACE
- Deposition of Copper Fine Particle by Cold Spray Process
- 610 Formation of Disk Splat in Thermal Spraying
- Proportionate Normalized Least Mean Square Algorithms Based on Coefficient Difference
- A Variable Step-Size Proportionate NLMS Algorithm for Identification of Sparse Impulse Response
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- Synthesis and Characterization of Nanocrystalline Iron Aluminide Intermetallic Compounds
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- Cold spray deposition on the thermoplastic and thermosetting polymer substrates : A comparative study