Automatic FIR Filter Design Method and Tool based on Genetic Algorithms

Abstract

A FIR Filter design method and its respective tool using genetic algorithms were developed. The main feature of this method is to offer a transparent mode for the user who doesn't know evolutionary computation, as well as its parameters. The user inputs the filter specifications and gets a sub-optimal result in an average number of four attempts. The sub-optimal criterion was based on the Rabiner, Parks and McClellan algorithm and the implemented software was built using the GALOPPS tool

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