Design IIR digital filters using Quantum-behaved Particle Swarm Optimization

被引：0
|
作者：
Fang, Wei [1 ]
Sun, Jun [1 ]
Xu, Wenbo [1 ]
机构：
[1] So Yangtze Univ, Sch Informat Technol, Ctr Intelligent & High Performance Comp, Wuxi 214122, Jiangsu, Peoples R China
来源：
ADVANCES IN NATURAL COMPUTATION, PT 2 | 2006年 / 4222卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Design IIR digital filters with arbitrary specified frequency is a multi-parameter optimization problem. In this paper, we employ our proposed method, Quantum-behaved Particle Swarm Optimization (QPSO), to solve the IIR digital filters design problem. QPSO, which is inspired by the fundamental theory of Particle Swarm Optimization and quantum mechanics, is a global convergent stochastic searching technique. The merits of the proposed method such as global convergent, robustness and rapid convergence are demonstrated by the experiment results on the low-pass and band-pass IIR filters.
引用
收藏
页码：637 / 640
页数：4
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