Title :
Monte Carlo methods for signal processing: a review in the statistical signal processing context
Author :
Doucet, Arnaud ; Wang, Xiaodong
Author_Institution :
Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC, Canada
Abstract :
In this article, MCMC (Markov chain Monte Carlo methods) and SMC (sequential Monte Carlo methods) are introduced to sample and/or maximize high-dimensional probability distributions. These methods enable to perform likelihood or Bayesian inference for complex non-Gaussian signal processing problems.
Keywords :
Bayes methods; Markov processes; Monte Carlo methods; signal processing; Bayesian inference; Markov chain Monte Carlo methods; complex nonGaussian signal processing problems; sequential Monte Carlo methods; Bayesian methods; Biomedical signal processing; Maximum likelihood estimation; Multidimensional signal processing; Multidimensional systems; Optimization methods; Probability distribution; Random variables; Signal processing; Signal processing algorithms;
Journal_Title :
Signal Processing Magazine, IEEE
DOI :
10.1109/MSP.2005.1550195
