Steady-state behavior of the improved normalized subband adaptive filter algorithm and its improvement in under-modeling

被引：0
|
作者：
Yi Yu
Haiquan Zhao
Lu Lu
机构：
[1] Southwest Jiaotong University,School of Electrical Engineering
来源：
Signal, Image and Video Processing | 2018年 / 12卷
关键词：
Colored input; Deficient length adaptive filter; Improved normalized subband adaptive filter algorithm; Mean square deviation; Steady-state performance;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In practice, adaptive filter could work in an under-modeling scenario, meaning that its length is less than that of the unknown system. In this realistic situation, therefore, the existing analysis for the improved normalized subband adaptive filter (INSAF) algorithm is not applicable. To this end, this paper analyzes the mean square steady-state performance of the INSAF for under-modeling. In addition, we propose a variable step size INSAF algorithm suitable for under-modeling scenario, to obtain fast convergence rate and low steady-state error. Simulation results have supported our theoretical analysis and proposed algorithm.
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页码：617 / 624
页数：7
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