Genetic algorithms are search methods based on principles of natural selection and genetics. These encode the decision variables of a search problem into finite-length strings. The strings are referred to as chromosomes and the alphabets are referred to as genes. This paper presents the design of IIR filter using GA. To formulate GA capable of designing an IIR filter, various constraints has been developed for the desired fitness function. The proposed algorithm has been tested for Butterworth filter. The magnitude response of the designed Butterworth IIR filter almost matches the desired response with an error 2e-6%. This shows the accuracy of the proposed algorithm. . Comparison of the pole-zero plot shows that there is very small error between the pole-zero placements in the desired and designed filters. Also the fitness function has converged with 1300 generations and achieve minimum value of is approximately 3e-32.
Article Details
Unique Paper ID: 142472
Publication Volume & Issue: Volume 2, Issue 2
Page(s): 190 - 194
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