Noise Constrained Data-Reusing Adaptive Algorithms for System Identification

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概要

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• We present a new framework of the data-reusing (DR) adaptive algorithms by incorporating a constraint on noise, referred to as a noise constraint. The motivation behind this work is that the use of the statistical knowledge of the channel noise can contribute toward improving the convergence performance of an adaptive filter in identifying a noisy linear finite impulse response (FIR) channel. By incorporating the noise constraint into the cost function of the DR adaptive algorithms, the noise constrained DR (NC-DR) adaptive algorithms are derived. Experimental results clearly indicate their superior performance over the conventional DR ones.

• 2012-06-01

著者

• CHOI Young-Seok

  Department of Electronic Engineering, Gangneung-Wonju National University

• SONG Woo-Jin

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

関連論文

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• Noise Constrained Data-Reusing Adaptive Algorithms for System Identification
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