DocumentCode
2519891
Title
FIR Digital Filters Design Based on Quantum-behaved Particle Swarm Optimization
Author
Fang, Wei ; Sun, Jun ; Xu, Wenbo ; Liu, Jing
Author_Institution
Center of Intelligent & High Performance Comput., Southern Yangtze Univ.
Volume
1
fYear
2006
fDate
Aug. 30 2006-Sept. 1 2006
Firstpage
615
Lastpage
619
Abstract
FIR digital filters design involves multi-parameter optimization, on which the existing optimization algorithm doesn´t work efficiently. This paper focuses on employing the proposed quantum-behaved particle swarm optimization (QPSO) to design FIR digital filters. QPSO is a global stochastic searching technique that can find out the global optima of the problem more rapidly than original PSO. After describing the origin and development of QPSO, we present how to use it in FIR digital filters design. It has been demonstrated by experiment results that QPSO outperforms the PSO and genetic algorithm (GA) for the problem
Keywords
FIR filters; particle swarm optimisation; quantum computing; search problems; stochastic processes; FIR digital filter design; QPSO; multiparameter optimization; quantum-behaved particle swarm optimization; stochastic search technique; Algorithm design and analysis; Convergence; Design optimization; Digital filters; Finite impulse response filter; Frequency; Genetic algorithms; High performance computing; Particle swarm optimization; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location
Beijing
Print_ISBN
0-7695-2616-0
Type
conf
DOI
10.1109/ICICIC.2006.77
Filename
1691875
Link To Document