Title :
Blind identification of Volterra-Hammerstein systems
Author :
Kalouptsidis, Nicholas ; Koukoulas, Panos
Author_Institution :
Dept. of Informatics & Telecommun., Athens Univ., Greece
fDate :
28 Sept.-1 Oct. 2003
Abstract :
This paper is concerned with the blind identification of Volterra-Hammerstein systems excited by zero mean white Gaussian inputs. A new method is developed for the determination of the Volterra kernels. Output cumulants of order twice the nonlinearity degree of the system are employed.
Keywords :
Gaussian processes; higher order statistics; identification; linear systems; multivariable systems; Volterra-Hammerstein systems; blind identification; zero mean white Gaussian inputs; Automation; Biological system modeling; Biomedical signal processing; Informatics; Kernel; Nonlinear systems; Power system modeling; Radar signal processing; Stochastic processes; System identification;
Conference_Titel :
Statistical Signal Processing, 2003 IEEE Workshop on
Print_ISBN :
0-7803-7997-7
DOI :
10.1109/SSP.2003.1289379
