Title :
An Orthogonal Functional Network for Function Approximation
Author :
Zhou, Yongquan ; Lu, Xueyan ; Xie, Zhucheng ; Liu, Bai
Author_Institution :
Coll. of Math. & Comput. Sci., Guangxi Univ. for Nat., Nanning
Abstract :
In this paper, a novel orthogonal functional network is proposed, it is a recently introduced extensive of functional networks. A learning algorithm of orthogonal functional network is proposed, the learning of functional parameters use Lagrange multipliers by means of auxiliary function and solving a system of linear equations obtain parameters. An experiment in approximating functions is given. The results show that the learning algorithm presented in the paper has excellent performance in approximation error.
Keywords :
function approximation; learning (artificial intelligence); Lagrange multipliers; approximation error; function approximation; linear equations; orthogonal functional network; Approximation algorithms; Approximation error; Computer networks; Equations; Function approximation; Intelligent networks; Neural networks; Neurons; Polynomials; Predictive models; function approximation.; functional network; functional parameters; learning algorithm; orthogonal functional network;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
DOI :
10.1109/ICICTA.2008.164
