Title :
Genetic Algorithm Based Adaptive System Identification
Author :
Karaboga, Nurhan ; Cetinkaya, Bahadir
Author_Institution :
Erciyes Univ., Kayseri
Abstract :
In this paper, the application of adaptive system identification based on genetic algorithm is realized. A high order unknown plant is modeled with a lower order adaptive finite impulse response (FIR) filter. Also, a performance comparison has been made between the conventional gradient based least mean square (LMS) algorithm and genetic algorithm (GA). Simulation results show that the genetic algorithm based design method has a better performance in terms of convergence speed and error performance.
Keywords :
FIR filters; adaptive filters; adaptive systems; convergence of numerical methods; genetic algorithms; identification; FIR filter; adaptive finite impulse response filter; adaptive system identification; convergence speed; error performance; genetic algorithm; high order unknown plant; Adaptive filters; Adaptive systems; Convergence; Design methodology; Finite impulse response filter; Gaussian noise; Genetic algorithms; Least squares approximation; System identification;
Conference_Titel :
Signal Processing and Communications Applications, 2007. SIU 2007. IEEE 15th
Conference_Location :
Eskisehir
Print_ISBN :
1-4244-0719-2
Electronic_ISBN :
1-4244-0720-6
DOI :
10.1109/SIU.2007.4298810
