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FIR Digital Filters Design Based on Quantum-behaved Particle Swarm Optimization
Beijing, China August 30-September 01
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICICIC.2006.77First International Conference on Inn ...
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Wei Fang, Southern Yangtze University
Jun Sun, Southern Yangtze University
Wenbo Xu, Southern Yangtze University
Jing Liu, Southern Yangtze University
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.
Citation:
Wei Fang, Jun Sun, Wenbo Xu, Jing Liu, "FIR Digital Filters Design Based on Quantum-behaved Particle Swarm Optimization," icicic, vol. 1, pp.615-619, First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06), 2006
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