Optimization of weighted myriad filters with differential evolution algorithm

Derivative-based algorithms, called classical algorithms, for optimization of weighted myriad (WMy) filters which are robust nonlinear filters in impulsive noisy environments are presented in literature. In this study, (WMy) filters that have various window lengths are optimized with differential evolution algorithm (DEA) that is known as a derivative-free based and evolutionary algorithm. The main contribution of this paper is to propose a novel strategy that is based on using the DEA in optimization of the parameters of nonlinear WMy filters. The results of proposed optimization studies are compared with a classical algorithm presented in literature. According to the simulation results; DEA has better performance than classical algorithm in optimization studies and also WMy filters optimized with DEA have ability of effectively suppressing the impulsive noisy environments.