Optimal IIR filter design using Gravitational Search Algorithm with Wavelet Mutation

This paper presents a global heuristic search optimization technique, which is a hybridized version of the gravitational search algorithm (gsa) and wavelet mutation (wm) strategy. thus, the gravitational search algorithm with wavelet mutation (gsawm) was adopted for the design of an 8th-order infinite impulse response (iir) filter. gsa is based on the interaction of masses situated in a small isolated world guided by the approximation of newtonian’s laws of gravity and motion. each mass is represented by four parameters, namely, position, active, passive and inertia mass. the position of the heaviest mass gives the near optimal solution. for better exploitation in multidimensional search spaces, the wm strategy is applied to randomly selected particles that enhance the capability of gsa for finding better near optimal solutions. an extensive simulation study of low-pass (lp), high-pass (hp), band-pass (bp) and band-stop (bs) iir filters unleashes the potential of gsawm in achieving better cut-off frequency sharpness, smaller pass band and stop band ripples, smaller transition width and higher stop band attenuation with assured stability