Optimization of FIR Filters using Genetic Algorithm Technique
This project deals with the involvement of Genetic Algorithm and its efficient optimizing techniques in the
Modern and Upcoming Technologies. It finds its varied application in artificial intelligence and various optimization tools
including google maps. Genetic Algorithm is based on the Darwin theory of “Survival of The Fittest” wherein the fittest
species among the group or population are crossed with respect to the fitness function and the mutations among the
reproduced individuals helps in achieving the desired optimized result.Genetic Algorithm works in various stages which
includes Selection, Reproduction, Crossover and Mutation as discussed previously. Here in this project we are using
“MATLAB Software” to achieve the desired Optimization Using GENETIC ALGORITHM. The Objective Equation is
coded in the MATLAB interface where we have taken two input variables whose values have to be optimized After the
MATLAB code is run, The Inbuilt Optimization Tool in MATLAB Software provides us the best optim value of the input
entities or variables of the objective equation. The best optim value of the input entities or variables of the Equation achieved
using Genetic Algorithm technique can be used to provide accurate and best possible results.
Keywords - Selection, Reproduction, Crossover, Optimization tool, Darwin Theory.