A Variable Error Data Normalized Step-Size LMS Adaptive Filter Algorithm : Analysis and Simulations

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概要

• 論文の詳細を見る

• This paper investigates noise reduction performance and performs convergence analysis of a Variable Error Data Normalized Step-Size Least Mean Square (VEDNSS LMS) algorithm. Adopting VEDNSS LMS provides fast convergence at early stages of adaptation while ensuring small final misadjustment. An analysis of convergence and steady-state performance for zero-mean Gaussian inputs is provided. Simulation results comparing the proposed algorithm to existing algorithms indicate its superior performance under various noise and frequency environments.

• 2009-01-01

著者

• Hong Kwang-seok

  Sungkyunkwan University

• Hong Kwang-seok

  Sungkyunkwan Univ.

• PARK Chee-Hyun

  Sungkyunkwan University

• PARK Chee-Hyun

  Sungkyunkwan Univ.

関連論文

• A Modified Variable Error-Data Normalized Step-Size LMS Adaptive Filter Algorithm
• A Variable Error Data Normalized Step-Size LMS Adaptive Filter Algorithm : Analysis and Simulations
• Squared Range Weighted Least Squares Source Localization Based on the Element-Wise and Vector-Wise Orthogonality Principles

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