Parameter identification to an approximated function of the Weierstrass approximation formula

Author

Tang, Jia ; Chen, Jing ; Zhou, Xiaoying

Author_Institution

Wuxi Prof. Coll. of Sci. & Technol., Wuxi, China

fYear

2012

fDate

23-25 May 2012

Firstpage

935

Lastpage

938

Abstract

In Weierstrass approximation theorem, a continuous function can be approximated by an algebraic polynomial. In this paper, we use the stochastic gradient identification algorithm and the recursive least squares algorithm to estimate the parameters of the algebraic polynomial. In order to improve the convergence rate and the computational effort, two modified stochastic gradient algorithms are given. The proposed approaches are illustrated by a simulation example.

Keywords

convergence of numerical methods; gradient methods; least squares approximations; polynomial approximation; recursive estimation; stochastic processes; Weierstrass approximation formula; algebraic polynomial; computational effort; continuous function; convergence rate; modified stochastic gradient identification algorithm; parameter estimation; recursive least squares algorithm; Algorithm design and analysis; Approximation algorithms; Convergence; Least squares approximation; Parameter estimation; Polynomials; Identification model; Parameter estimation; Recursive least squares; Stochastic gradient; Weierstrass approximation theorem;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2012 24th Chinese

Conference_Location

Taiyuan

Print_ISBN

978-1-4577-2073-4

Type

conf

DOI

10.1109/CCDC.2012.6244146

Filename

6244146