A Survey of Stochastic Simulation and Optimization Methods in Signal Processing

Abstract : Modern signal processing (SP) methods rely very heavily on probability and statistics to solve challenging SP problems. SP methods are now expected to deal with ever more complex models, requiring ever more sophisticated computational inference techniques. This has driven the development of statistical SP methods based on stochastic simulation and optimization. Stochastic simulation and optimization algorithms are computationally intensive tools for performing statistical inference in models that are anal ytically intractable and beyond the scope of deterministic inference methods. They have been recently successfully applied to many difficult problems involving complex statistical models and sophisticated (often Bayesian) statistical inference techniques. This survey paper offers an introduction to stochastic simulation and optimization methods in signal and image processing. The paper addresses a variety of high-dimensional Markov chain Monte Carlo (MCMC) methods as well as deterministic surrogate methods, such as variational Bayes, the Bethe approach, belief and expectation propagation and approximate message passing algorithms. It also discusses a range of optimization methods that have been adopted to solve stochastic problems, as well as stochastic methods for deterministic optimization. Subsequently, area as of overlap between simulation and optimization, in particular optimization-within-MCMC and MCMC-driven optimization are discussed.
Document type :
Journal articles
Liste complète des métadonnées

Cited literature [156 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01312917
Contributor : Open Archive Toulouse Archive Ouverte (oatao) <>
Submitted on : Monday, May 9, 2016 - 11:54:08 AM
Last modification on : Friday, April 12, 2019 - 4:23:06 PM
Document(s) archivé(s) le : Tuesday, November 15, 2016 - 10:34:01 PM

File

pereyra_15732.pdf
Publication funded by an institution

Identifiers

Citation

Marcelo Alejandro Pereyra, Philip Schniter, Emilie Chouzenoux, Jean-Christophe Pesquet, Jean-Yves Tourneret, et al.. A Survey of Stochastic Simulation and Optimization Methods in Signal Processing. IEEE Journal of Selected Topics in Signal Processing, IEEE, 2015, vol. 10 (n° 2), pp. 224-241. ⟨10.1109/JSTSP.2015.2496908⟩. ⟨hal-01312917⟩

Share

Metrics

Record views

393

Files downloads

378