Bias-Free Adaptive IIR Filtering

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概要

• 論文の詳細を見る

• We present a new family of algorithms that solve the bias problem in the equation-error based adaptive infinite impulse response (IIR) filtering. A novel constraint, called the constant-norm constraint, unifies the quadratic constraint and the monic one. By imposing the monic constraint on the mean square error (MSE) optimization, the merits of both constraints are inherited and the shortcomings are overcome. A new cost function based on the constant-norm constraint and Lagrange multiplier is defined. Minimizing the cost function gives birth to a new family of bias-free adaptive IIR filtering algorithms. For example, two efficient algorithms belonging to the family are proposed. The analysis of the stationary points is presented to show that the proposed methods can indeed produce bias-free parameter estimates in the presence of white noise. The simulation results demonstrate that the proposed methods indeed produce unbiased parameter estimation, while being simple both in computation and implementation.

• 社団法人電子情報通信学会の論文
• 2001-05-01

著者

• Song Woo-jin

  Division Of Electronics And Computer Engineering Pohang University Of Science And Technology (postec

• Shin H‐c

  Korea Advanced Inst. Of Sci. And Technol. (kaist) Daejeon Kor

• SHIN Hyun-Chool

  Division of Electronics and Computer Engineering, Pohang University of Science and Technology (POSTE

• Song Woo-jin

  Division Of Electronics And Computer Engineering Pohang University Of Science And Technology (postec

• SONG Woo-Jin

  Division of Electrical and Computer Engineering, Pohang University of Science and Technology (POSTECH)

関連論文

• A Simple Adaptive Algorithm for Principle Component and Independent Component Analysis
• Bias-Free Adaptive IIR Filtering
• Noise Constrained Data-Reusing Adaptive Algorithms for System Identification
• Partial-Update Normalized Sign LMS Algorithm Employing Sparse Updates

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