Seeker Optimization Algorithm for Digital IIR Filter Design

被引：149

作者：

Dai, Chaohua ^{[1
]}

Chen, Weirong ^{[1
]}

Zhu, Yunfang ^{[2
]}

机构：

[1] SW Jiaotong Univ, Sch Elect Engn, Chengdu 610031, Peoples R China

[2] SW Jiaotong Univ, Dept Comp & Commun Engn, Emei 614202, Peoples R China

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2010年 / 57卷 / 05期

基金：

中国国家自然科学基金;

关键词：

Digital infinite-impulse-response (IIR) filter design; global optimization; heuristics; seeker optimization algorithm (SOA); system identification; PARTICLE SWARM OPTIMIZATION; DIFFERENTIAL EVOLUTION;

D O I：

10.1109/TIE.2009.2031194

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Since the error surface of digital infinite-impulseresponse (IIR) filters is generally nonlinear and multimodal, global optimization techniques are required in order to avoid local minima. In this paper, a seeker-optimization-algorithm (SOA)-based evolutionary method is proposed for digital IIR filter design. SOA is based on the concept of simulating the act of human searching in which the search direction is based on the empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. The algorithm's performance is studied with comparison of three versions of differential evolution algorithms, four versions of particle swarm optimization algorithms, and genetic algorithm. The simulation results show that SOA is superior or comparable to the other algorithms for the employed examples and can be efficiently used for IIR filter design.

引用

页码：1710 / 1718

页数：9