Optimal FIR Filter Design using Honey Badger Optimization Algorithm

Abstract

This paper employs the Honey Badger Algorithm (HBA) to find the optimized coefficients of FIR linear phase filters, i.e., Band Pass Filter (BPF), Band Stop Filter (BSF), Low Pass Filter (LPF), and High Pass Filter (HPF). With its quick convergence and reduced number of tuning parameters, HBA is a promising new metaheuristic method. HBA, which imitates the foraging behavior of the honey badger is likely to maintain the balance between the two phrases of exploration and exploitation. HBA computes the optimal coefficients of the specified filter using the digging and honey-searching modes. As a consequence, the provided work is able to accomplish the ideal frequency performance characteristics with the maximum stop band attenuation and the negligible pass band ripple. In other words, the HBA designed filter can perform better than filters using other methods because it has fewer ripples in passband and narrower transition width, which enhances its frequency response.