Overview of intelligent optimization algorithm design of FIR digital filter

Abstract

This article summarizes the intelligent optimization algorithm of finite impulse response digital filter(FIR). The main idea of optimization design is to transform the digital filter design problem into the error function minimization problem. Compared with the traditional methods, this method is easier to determine the boundary frequencies of the pass-band and stop-band, to reduce the computational complexity and the errors of amplitude frequency response both in pass-band and stop-band. This paper analyzes and compares the characteristics of genetic，evolution，and particle swarm algorithms in the design of FIR digital filters from the perspectives of convergence speed, pass-band ripple，and stop-band attenuation. It focuses on the improvement strategy of the weight of inertia in particle swarm algorithm.

Keywords

• fir digital filter
• intelligent algorithm
• filter design
• optimization
• error function