Performance comparisons of three IIR structures for adaptive system identification based on genetic algorithms

Genetic Algorithms (GA's) are based on the principles of natural selection and natural genetics that originate in biology. The Genetic Algorithm (GA) has been used for IIR adaptive system identification to deal with its multimodal error surface. The Genetic Algorithm (GA) can perform well in many different IIR adaptive filter structures, while the Gradient Algorithm often does not perform well in these situations. This paper focuses on the performances of three different structures of IIR filters based on the conventional Genetic Algorithm (GA) and the more specialized Multi-Parents Genetic Algorithm (MPGA).