Efficient FIR filter designs using constrained genetic algorithms based optimization

In this work, an application of constrained genetic algorithm (CGA) based optimization approach has been explored for design of low pass and high pass finite impulse response (FIR) digital filters. To accomplish the task of optimal filter design, a novel constraint function has been proposed and integrated with the fitness function in CGA environment. CGA minimizes the fitness function under supervision of the proposed constraint. Performances of designed FIR digital filters have been compared with the recently published designs of same order and the intensive MATLAB simulations based investigations have confirmed the superiority of the proposed designs in terms of smaller pass band and stop band ripples.