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
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;
Conference_Titel :
Wireless, Mobile and Sensor Networks, 2007. (CCWMSN07). IET Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-86341-836-5
