A fast evolutionary programming for adaptive FIR filter

被引：1
|
作者：
Zhang, J [1 ]
Liao, XF [1 ]
Zhao, H [1 ]
Yu, JB [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Elect Engn, Chengdu 610054, Peoples R China
来源：
2004 INTERNATIONAL CONFERENCE ON COMMUNICATION, CIRCUITS, AND SYSTEMS, VOLS 1 AND 2: VOL 1: COMMUNICATION THEORY AND SYSTEMS - VOL 2: SIGNAL PROCESSING, CIRCUITS AND SYSTEMS | 2004年
关键词：
evolution; evolutionary programming; adaptive FIR filter; optimization of parameter;
D O I：
10.1109/ICCCAS.2004.1346376
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The LMS algorithm is commonly used in the optimum design of the adaptive filter. Because the LMS adaptive algorithm is a simple algorithm and it can be realized easily. But the convergence behavior and maladjustment of the LMS algorithm is seriously affected by the step-size, and the optimum parameter of step-size can't be calculated easily. Evolutionary programming is an optimum algorithm in which the optimization of N-dimensions real-numbers are research objects. In this paper, FIR Filter is an example. In the design of the Adaptive Filter, we use a fast Evolutionary Programming Algorithm. Cauchy mutation takes the place of Gauss mutation for improving the speed of the convergence. This algorithm is not depend on any parameter; W can get a good result by the simulation and indicate the validity of the algorithm.
引用
收藏
页码：1136 / 1140
页数：5
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