Title :
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
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;
Conference_Titel :
Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-4120-7
DOI :
10.1109/ACSSC.1993.342506
