Low-pass filter approximation with evolutionary techniques

In this work, two evolutionary techniques, Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms are used to optimize the denominator coefficients of the low-pass filter transfer function. Optimum selection of the coefficients will approximate the transfer function to ideal characteristic. Two different order of transfer functions are taken into consideration. Compared to conventional methods, both PSO and ABC minimize the approximation error in a short computation time.