DocumentCode
485265
Title
A blind approach to nonlinear system identification
Author
Zhu, Y.F. ; Tan, H.Z. ; Pin Wan ; Zhang, Ye
Author_Institution
Fac. of Autom., Guangdong Univ. of Technol., Guangzhou
fYear
2007
fDate
12-14 Dec. 2007
Firstpage
209
Lastpage
212
Abstract
The paper combines the least squares support vector machines (LS-SVM) with the system output oversampling technique to realize the blind nonlinear system identification. The given distribution of the inputs is employed to perform this novel algorithm. The LS-SVM based mathematical approximation provides an adequate modeling of the unknown nonlinear system given the distribution knowledge of the system inputs. Simulation results demonstrate the effectiveness of this approach.
Keywords
approximation theory; identification; least mean squares methods; nonlinear systems; signal sampling; support vector machines; least squares support vector machines; mathematical approximation; nonlinear system identification; system output oversampling technique; Blind identification; Nonlinear systems; Oversampling; Support vector machines;
fLanguage
English
Publisher
iet
Conference_Titel
Wireless, Mobile and Sensor Networks, 2007. (CCWMSN07). IET Conference on
Conference_Location
Shanghai
ISSN
0537-9989
Print_ISBN
978-0-86341-836-5
Type
conf
Filename
4786174
Link To Document