Title :
The hybrid method for determining an adaptive step size of the unknown system identification using genetic algorithm and LMS algorithm
Author :
Kim, Dongsoon ; Lee, Taekjoo ; Lim, Dong-Kuk ; Jung, Duckjin
Author_Institution :
Integrated Circuit Res. Lab., Inha Univ., Inchon, South Korea
Abstract :
We describe the application of a genetic algorithm (GA) to the problem of parameter optimization for an adaptive finite impulse response (FIR) filter combining genetic algorithm (GA) and least mean square (LMS) algorithm. For system identification problem, LMS algorithm computes the filter coefficients and GA search the optimal step-size adaptively. Because step-size influences on the stability and performance, so it is necessary to apply method that can control it. The simulation results of the GA were compared to the traditional LMS algorithm. We obtained that genetic algorithm was clearly superior (in accuracy) in most cases.
Keywords :
FIR filters; adaptive filters; genetic algorithms; identification; least mean squares methods; optimisation; search problems; GA search; LMS algorithm; adaptive finite impulse response filter; adaptive step size; filter coefficients; genetic algorithm; hybrid method; least mean square algorithm; optimal step-size; parameter optimization; unknown system identification; Adaptive filters; Application specific integrated circuits; Biological cells; Finite impulse response filter; Genetic algorithms; Genetic mutations; Least squares approximation; Mathematical model; Stability; System identification;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1198172
