Design IIR digital filters using quantum-behaved particle swarm optimization

  • Authors:

  • Wei Fang;Jun Sun;Wenbo Xu

  • Affiliations:

  • Center of Intelligent and High Performance Computing, School of Information Technology, Southern Yangtze University, Wuxi, Jiangsu, China;Center of Intelligent and High Performance Computing, School of Information Technology, Southern Yangtze University, Wuxi, Jiangsu, China;Center of Intelligent and High Performance Computing, School of Information Technology, Southern Yangtze University, Wuxi, Jiangsu, China

  • Venue:
  • ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
  • Year:
  • 2006

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Abstract

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.