Chaotic particle swarm optimization for FIR filter design
Zhongkai Zhao, Hongyuan Gao, Yanqiong Liu · 2011
FIR digital filters design involves multi-parameter optimization, on which the existing optimization algorithm does not work efficiently. This paper focuses on employing the proposed chaotic particle swarm optimization (CPSO) to design FIR digital filters. CPSO is a global stochastic searching technique which is able to find out the global optima more rapidly than original PSO. After describing the theory and method of CPSO, we present how to use it in FIR digital filters design. It has been demonstrated by experiment results that CPSO outperforms the PSO and quantum particle swarm optimization (QPSO) for the problem of filter design.