Opposition aided Cat Swarm Optimization Algorithm for Digital IIR Low Pass Filter Design

This paper undertakes the designing of optimal and stable digital infinite impulse response (IIR) low pass (LP) filter by employing the cat swarm optimization (CSO) technique with oppositional learning. CSO is a population based global optimization technique which possesses global as well as local search capabilities. The conventional optimization techniques used to design the digital IIR filter generally got caught in the local minima as the error surface of the digital IIR filter is non linear and multimodal because of the presence of the denominator terms. Although, CSO possesses better parameter estimation and has a much higher convergence speed than genetic algorithm and particle swarm optimization algorithm, it requires a higher computation time because the local and global searches are carried out independently in each iteration. So, in order to reduce the computational time this paper attempts to incorporate the concept of opposition based learning (OBL) strategy. The main idea behind OBL is the simultaneous consideration of an estimate and its corresponding opposite estimate in order to achieve a better approximation for the current candidate solution. The proposed opposition based cat swarm optimization method starts with some initial random solutions that are improved by moving towards optimal solution. The computation time is improved by starting with a better solution by simultaneously checking the opposite solution in the search space. Here, the multicriterion optimization is utilized as the design criterion that undertakes the minimization of magnitude approximation error and minimization of ripple magnitudes while satisfying the stability constraints that are imposed during the design process. The developed algorithm strives to find the optimal filter coefficients which are approximately close to the desired filter response. The computational results reveal that the proposed algorithm is capable of designing the stable and optimal digital IIR LP filter structure that is superior to the designs presented by other algorithms and can also be efficiently applied for the design of higher order LP filter.