Blind Identification of Weak Nonlinear System Based on Normalized Kurtosis

Author

Huxiao ; Mahong

Author_Institution

Wuhan Nat. Laborary for Optoelectron., HuaZhong Univ. of Sci. & Technol., Wuhan, China

Volume

3

fYear

2010

fDate

12-14 April 2010

Firstpage

12

Lastpage

16

Abstract

This paper studies normalized kurtosis and its application in weak nonlinear system identification. According to the definition of normalized kurtosis and its properties, the memory effect and nonlinear order influences on normalized kurtosis are derived theoretically, and simulation results are given. Accordingly, this paper proposes a method in weak nonlinear system identification by using normalized kurtosis variation with varying system characteristics. Finally, this paper describes the potential advantage of proposed method.

Keywords

blind source separation; statistical analysis; blind identification; memory effect; nonlinear order; normalized kurtosis variation; varying system characteristics; weak nonlinear system identification; Autocorrelation; Higher order statistics; Mobile communication; Nonlinear systems; Parameter estimation; Power system modeling; Receivers; Signal processing algorithms; System identification; Technological innovation; Normalized kurtosis; memory effect; nonlinear order; system identification; weak nonlinear system;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications and Mobile Computing (CMC), 2010 International Conference on

Conference_Location

Shenzhen

Print_ISBN

978-1-4244-6327-5

Electronic_ISBN

978-1-4244-6328-2

Type

conf

DOI

10.1109/CMC.2010.172

Filename

5471306