Filter design using insertion loss method and Particle Swarm Optimization algorithm

A filter design using insertion loss method (ILM) and Particle Swarm Optimization algorithm (PSO) is presented in the paper. ILM is generally a preferred technique for the filter design with an arbitrary number of elements. This method can be used to create the filter which has different types of frequency responses. However, this procedure is not practical for a large number of elements. PSO algorithm can be a useful procedure for calculating values in filters with a large number of elements. This paper presents the procedure which takes an advantage of ILM for filter design and PSO for determination an unknown value in filters with large number of elements. This is suitable approach for filter design with an arbitrary shape of cutoff frequency and pass band.

1. INTRODUCTION

Filters are two-port networks used to control the frequency response and they are present in just about every piece of electronic equipment (radios, television, analog-to-digital converters, computers etc.). There are four possible frequency responses: lowpass, highpass, bandpass and bandstop. Filters can be analog or digital. Furthermore, analog filters can be passive or active. Passive filters use only resistors, capacitors, and inductors. Very simple analog lowpass or highpass filters can be constructed from resistors and capacitors (RC) network. Both analog and digital filters can be considered as “black box” (Fig 1.) with signals which are input on one side of the box and output on the other side. Fig. 1. Filter as “black box” with transfer function