Title :
Adaptive Bayesian signal processing - a sequential Monte Carlo paradigm
Author :
Wang, Xiaodong ; Chen, Rong ; Liu, Jun S.
Author_Institution :
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
We provide a general framework for using Monte Carlo methods in dynamic systems and discuss its wide application in adaptive signal processing. All of these methods are partial combinations of three ingredients: importance sampling and resampling, rejection sampling and Markov chain iterations. Examples from target tracking and digital communication applications are provided to demonstrate the effectiveness of these novel statistical signal processing techniques
Keywords :
Bayes methods; Markov processes; adaptive signal processing; digital communication; importance sampling; iterative methods; radar signal processing; signal sampling; target tracking; Bayesian signal processing; Markov chain iterations; adaptive signal processing; digital communication; dynamic systems; importance resampling; importance sampling; rejection sampling; sequential Monte Carlo methods; statistical signal processing; target tracking; Adaptive signal processing; Bayesian methods; Equations; Filtering; Inference algorithms; Monte Carlo methods; Signal sampling; Statistics; Target tracking; Yttrium;
Conference_Titel :
Statistical Signal and Array Processing, 2000. Proceedings of the Tenth IEEE Workshop on
Conference_Location :
Pocono Manor, PA
Print_ISBN :
0-7803-5988-7
DOI :
10.1109/SSAP.2000.870119
