Low complexity multiobjective finite impulse response filter design using Salp swarm algorithm and its improved version

Abstract

Recent trend indicates that the assessment of low complexity is crucial for an effectual design of digital filter. Earlier the existing algorithms solely focused on reducing the pass band ripples and the stop band ripples in spite of the requirement of low implementation complexity in finite impulse response (FIR) filter design. In this regard, the optimization‐based FIR filter using multiobjective improved Salp swarm optimization algorithm have been designed. The proposed method not only minimizes the ripples of pass band and stop band but also minimizes the transition band, number of sparsity, which is used to implement a FIR filter that abides the specified frequency. The nondominated solution of filter design has a set of an optimum solution as pareto front that maintains the trade‐off between the various specifications. The designed FIR filter has been compared with other reported method to validate the applicability of the proposed method. The evaluation and analysis have been performed regrading minimum pass band ripples, minimum stop band ripple, minimum transition band, and implementation complexity. To prove the practical applicability of the proposed method, the designed FIR filters have been implemented in Xilinx ISE14.7 (Virtex‐VII) environment. The comparison result shows that the proposed method performs better than all other reported method in achieving minimum ripples and implementation complexity.