A new adaptive blind channel identification algorithm

被引：2
|
作者：
Peng, Dezhong [2 ]
Xiang, Yong [1 ]
Yi, Zhang [2 ]
机构：
[1] Deakin Univ, Sch Informat Technol & Engn, Geelong, Vic 3217, Australia
[2] Univ Elect Sci & Technol China, Computat Intelligence Lab, Sch Engn & Comp Sci, Chengdu 610054, Peoples R China
来源：
CHAOS SOLITONS & FRACTALS | 2009年 / 41卷 / 01期
基金：
美国国家科学基金会; 澳大利亚研究理事会;
关键词：
CONVERGENCE ANALYSIS; LEARNING ALGORITHM; NEURAL-NETWORKS; STABILITY; CONSTANT; PCA; MCA;
D O I：
10.1016/j.chaos.2008.01.002
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
This paper addresses the blind identification of single-input multiple-output (SIMO) finite-impulse-response (FIR.) systems. We first propose a new adaptive algorithm for the blind identification of SIMO FIR systems. Then, its convergence property is analyzed systematically. It is shown that under some mild conditions, the proposed algorithm is guaranteed to converge in the mean to the true channel impulse responses in both noisy and noiseless cases. Simulations are carried out to demonstrate the theoretical results. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码：354 / 359
页数：6
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