A Review: Analysis the FIR filter using an Adaptive Techniques Method

Genetic Algorithm (GA) is a calculus free optimization technique based on principles of natural selection for reproduction and various evolutionary operations such as crossover, and mutation. Various steps involved in carrying out optimization through GA are described. Three applications, viz. finding maximum of a mathematical function, obtaining estimates for a multiple linear regression model, and fitting a nonlinear statistical model through GA procedure, are discussed. Finally, results are compared to those obtained from standard solution techniques. Classical search and optimization methods demonstrate a number of difficulties when faced with complex problems. The major difficulty arises when one algorithm is applied to solve a number of different problems.