A novel self-adaptive differential evolution algorithm for efficient design of multiplier-less low-pass FIR filter

摘要

Variety of real-world optimization problems can be successfully solved by employing a powerful technique, called Differential Evolution (DE) algorithm. The popularity of DE has grown tremendously since its inception as it includes a very few number of control parameters. However, the selection or tuning of these parameters plays a crucial role in determining the performance of the algorithm in terms of its convergence behaviour. In this paper, a novel Self-Adaptive DE (SADE) approach has been proposed for the design of a multiplier-less low-pass linear-phase FIR filter to improve the computational efficiency of the algorithm. For this purpose, the convergence behaviour of the SADE technique has been presented and it has been compared with that of traditional DE technique. Additionally, the performance of the SADE-optimized filter has been evaluated in terms of its magnitude response. The corresponding magnitude response for the DE-optimized filter has also been presented for comparison. It has been established that the proposed SADE algorithm outperforms the traditional DE for this particular design problem.