IIR Filter Design Using Multiobjective Artificial Bee Colony Algorithm
Rija Raju, Hon Keung Kwan · 2018
In this paper, IIR filters are designed using Gbest-guided Multiobjective Artificial Bee Colony algorithm (GMOABC). Artificial Bee Colony algorithm (ABC) is a stochastic optimization algorithm inspired by the food seeking behavior of honey bee colonies. Even though ABC algorithm can converge to a global optimum for complex problems, the time taken for convergence is longer than classical methods. Gbest guided multiobjective ABC algorithm can reduce the time taken for converging to global optimum and improves the quality of the solutions by tuning the search process towards the global best in each iteration. IIR filter design is a non-convex optimization problem and requires the optimization of both the magnitude and group delay. The results show that, GMOABC can achieve lower passband error and group delay error than the recent results obtained by other methods.