A full mean-square analysis of CNSAF algorithm for noncircular inputs

被引:7
|
作者
Wen, Pengwei [1 ]
Zhang, Sheng [2 ]
Du, Siyuan [2 ]
Qu, Boyang [1 ]
Song, Xiaowei [1 ]
机构
[1] Zhongyuan Univ Technol, Sch Elect & Informat Engn, Zhengzhou 450007, Henan, Peoples R China
[2] Southwest Jiaotong Univ, Sichuan Prov Key Lab Signal & Informat Proc, Chengdu 610031, Peoples R China
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2021年 / 358卷 / 15期
基金
美国国家科学基金会;
关键词
SUBBAND ADAPTIVE FILTER; PERFORMANCE ANALYSIS; DEVIATION ANALYSIS; LMS;
D O I
10.1016/j.jfranklin.2021.07.031
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A full performance analysis of complex normalized subband adaptive filter (CNSAF) algorithm will provide guidelines for designing the adaptive filter. However, because of the noncircular characteristic of complex-value signal, the complementary mean-square performance analysis of the CNSAF algorithm has not been presented in the literature. In order to give the detailed theoretical expressions of the CNSAF algorithm, the present study first analyzes the mean-square deviation (MSD) with the energy conservation method, and then the complementary mean-square derivation (CMSD) behavior is given using pseudo-energy-conservation method. Analytical expressions are obtained for the transient MSD and CMSD of the CNSAF algorithm. Also, the steady-state MSD and CMSD are predicted based on the closed-form expressions. Besides, the analysis results are not constrained by the distribution of input signals. Finally, simulation results obtained for diffferent inputs present a good consistence with the analytical results. (c) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:7883 / 7899
页数:17
相关论文
共 50 条