Higher-order statistics-based estimation of moments of first passage time for Markov chains in its reverse problem

Author

Yu, Shi ; Xianda, Zhang

Author_Institution

Dept. of Autom., Tsinghua Univ., Beijing, China

fYear

1998

fDate

1998

Firstpage

435

Abstract

This paper presents a statistical approach for estimating the moments by using higher-order cumulants when the additive noise is Gaussian colored noise. It is shown that the kth-order moments of the noise samples are only related to the variance of the noise and that the estimators have the properties of unbiasedness and congruence. A numerical simulation is performed for constructing a Markov chain of continuous time parameters. The results show the validity of this algorithm

Keywords

Gaussian noise; Markov processes; higher order statistics; numerical analysis; parameter estimation; signal sampling; Markov chains; additive Gaussian colored noise; congruence; continuous time parameters; first passage time; higher-order cumulants; higher-order statistics; moment estimation; noise samples; noise variance; numerical simulation; reverse problem; statistical approach; unbiasedness; Additive noise; Automation; Colored noise; Distribution functions; Higher order statistics; Information processing; Intelligent systems; Laboratories; Numerical simulation; Physics;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Proceedings, 1998. ICSP '98. 1998 Fourth International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4325-5

Type

conf

DOI

10.1109/ICOSP.1998.770244

Filename

770244