DocumentCode
3356782
Title
Genetic Algorithm Based Adaptive System Identification
Author
Karaboga, Nurhan ; Cetinkaya, Bahadir
Author_Institution
Erciyes Univ., Kayseri
fYear
2007
fDate
11-13 June 2007
Firstpage
1
Lastpage
4
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/SIU.2007.4298810
Filename
4298810
Link To Document