FIR Digital Filters Design Based on Quantum-behaved Particle Swarm Optimization

  • Authors:
  • Wei Fang;Jun Sun;Wenbo Xu;Jing Liu

  • Affiliations:
  • Southern Yangtze University;Southern Yangtze University;Southern Yangtze University;Southern Yangtze University

  • Venue:
  • ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1
  • Year:
  • 2006

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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.