Title :
System identification via simultaneous perturbation stochastic approximation
Author :
Hirokami, Tatsuya ; Maeda, Yutaka
Author_Institution :
Dept. of Electr. Eng., Kansai Univ., Suita, Japan
Abstract :
The simultaneous perturbation stochastic approximation (SPSA) is an extension of Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. In SPSA, since all parameters are perturbed simultaneously, it is possible to modify the parameters with only two measurements of the evaluation function disregard of the dimension of the parameters. We propose a parameter identification algorithm using SPSA. Simulation result shows the feasibility of the identification approach proposed.
Keywords :
approximation theory; discrete time systems; linear systems; parameter estimation; stochastic processes; Kiefer Wolfowitz stochastic approximation algorithm; discrete linear system; parameter estimation; simultaneous perturbation; simultaneous perturbation stochastic approximation; stochastic approximation; system identification; Delay effects; Delay estimation; Equations; Linear systems; Neural networks; Noise measurement; Parameter estimation; Stochastic processes; Stochastic systems; White noise;
Conference_Titel :
SICE 2002. Proceedings of the 41st SICE Annual Conference
Print_ISBN :
0-7803-7631-5
DOI :
10.1109/SICE.2002.1195360