FIR filter design using Multiobjective Artificial Bee Colony algorithm

In this paper, general FIR filters are designed using multiobjective Artificial Bee Colony algorithm. Spherical pruning (SP) and physical programming (PP) techniques are combined together in the implementation of multiobjective Artificial Bee Colony algorithm. Physical programming converts the design objectives into an intuitive language and spherical pruning maintains diversity in the Pareto front. The design of general FIR filters require simultaneous optimization of magnitude and group delay errors and therefore can be formulated as a Multiobjective Optimization (MOO) problem. All the non-dominated solutions of the general FIR design problem can be approximated into a Pareto front. Numerical results show that, multiobjective Artificial Bee Colony algorithm can achieve lower passband, stopband, group delay errors when compared to those of spherical pruning Multiobjective Differential Evolution (spMODE-II).

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