Modified Cat Swarm Optimization Algorithm for Design and Optimization of IIR BS Filter

This paper proposes a solution methodology for the design of optimal and stable digital infinite impulse response (IIR) band stop (BS) filter by employing modified cat swarm optimization (CSO) algorithm. The error surface of digital IIR filters is non linear and multimodal because of the presence of the denominator terms. Therefore, the traditional filter design methods usually got stuck in the local minim. CSO is a novel population based global optimization technique which possesses global as well as local search capabilities. Here, the multicriterion optimization is used as the decisive factor that undertakes the minimization of magnitude approximation error and minimization of ripple magnitudes of pass band and stop band while satisfying the stability constraints that are imposed during the design process. For the intention of starting with an improved solution set, the opposition based learning strategy is incorporated in the conventional CSO. The developed algorithm is used to design the digital IIR band stop (BS) filter and attempts to find the optimal filter coefficients which are approximately close to the desired filter response. The computational results show that the proposed algorithm is capable of designing stable and optimal digital IIR BS filter structure that is better to the designs presented by other algorithms. Keywords— Digital IIR filter, cat swarm optimization algorithm, opposition based learning, filter design, multiparameter optimization.