Recursive computation of a posteriori density functions for arbitrary i.i.d. state noise and its application to impulsive interference mitigation

Author

Shen, Jun ; Nikias, Chrysostomos L.

Author_Institution

Signal & Image Process. Inst., Univ. of Southern California, Los Angeles, CA, USA

fYear

1993

fDate

1-3 Nov 1993

Firstpage

228

Abstract

Studies the a posteriori probability density function of the state of a discrete-time system. By applying the Bayesian law to the state and measurement equations of the stochastic system, the a posteriori density is obtained in closed-form and computed recursively for arbitrary i.i.d. state noise and binary measurement noise (or signal). As an example, the highly impulsive state process driven by the noise with α-stable distribution is estimated and significantly suppressed from the measurement

Keywords

Bayes methods; autoregressive processes; binary sequences; discrete time systems; interference suppression; random noise; recursive estimation; signal detection; state-space methods; stochastic processes; α-stable distribution; Bayesian law; a posteriori density functions; arbitrary iid state noise; binary measurement noise; closed-form; discrete-time system; highly impulsive state process; impulsive interference mitigation; stochastic system; Bayesian methods; Density functional theory; Density measurement; Equations; Image processing; Interference; Noise measurement; Probability density function; Random processes; Signal processing; State estimation; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-4120-7

Type

conf

DOI

10.1109/ACSSC.1993.342506

Filename

342506