Analog active filter component selection with nature inspired metaheuristics

The most crucial design step for analog active filter design is the optimal selection of passive component values due to manufactured constants. Since the search on possible combinations in preferred values for capacitors and resistors is an exhaustive process, it has to be automated with high accuracy within short computation time. In this work, two nature inspired metaheuristics, differential evolution (DE) and harmony search (HS) algorithms are utilized for optimal filter design considering different topologies and manufacturing series. Simulation results show that as global optimization methods both DE and HS minimize the total design error and reduce the elapsed time with respect to previously utilized methods.