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A Survey of Stochastic Simulation and Optimization Methods in Signal Processing

Pereyra, Marcelo Alejandro and Schniter, Philip and Chouzenoux, Emilie and Pesquet, Jean-Christophe and Tourneret, Jean-Yves and Hero, Alfred O. and McLaughlin, Steve A Survey of Stochastic Simulation and Optimization Methods in Signal Processing. (2015) IEEE Journal on Selected Topics in Signal Processing, 10 (2). 224-241. ISSN 1932-4553

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Official URL: http://dx.doi.org/10.1109/JSTSP.2015.2496908

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.

Item Type:Article
Additional Information:Thanks to IEEE editor. The definitive version is available at http://ieeexplore.ieee.org/ The original PDF of the article can be found at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7314898
HAL Id:hal-01312917
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Other partners > Ohio State University (USA)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > University of Bristol (UNITED KINGDOM)
Other partners > Heriot-Watt University (UNITED KINGDOM)
Other partners > Université Paris-Est Marne-La-Vallée - UPEM (FRANCE)
Other partners > University of Michigan - U-M (USA)
Laboratory name:
Statistics:download
Deposited By: Jean-yves TOURNERET
Deposited On:09 May 2016 09:53

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