Differential Cultural Algorithm for Digital Filters Design

摘要

FIR and IIR digital filters design involve multi-parameter optimization, on which some existing intelligent algorithms don't work efficiently. This paper focuses on employing the proposed differential cultural (DC) algorithm to design FIR and IIR digital filters. DC is a global stochastic searching technique that can find out the global optima of the problem more rapidly. After describing the theory and method of DC, we present how to use it in FIR and IIR digital filters design. It has been proved by simulation experiments that DC outperforms the particle swarm optimization (PSO), quantum particle swarm optimization (QPSO) and adaptive quantum particle swarm optimization (AQPSO) for the problem of filter design.