Committee login






Small thumbnail

Nonlinear Theory of Elastic Plates

Small thumbnail

Exterior Algebras

Elementary Tribute to Grassmann's Ideas

Small thumbnail

From Pinch Methodology to Pinch-Exergy Integration of Flexible Systems

Thermodynamics – Energy, Environment, Economy Set

Small thumbnail

Data Treatment in Environmental Sciences

Multivaried Approach

Small thumbnail

Gas Hydrates 1

Fundamentals, Characterization and Modeling

Small thumbnail

Smart Decisions in Complex Systems

Small thumbnail

Chi-squared Goodness-of-fit Tests for Censored Data

Stochastic Models in Survival Analysis and Reliability Set – Volume 3

Small thumbnail

Baidu SEO

Challenges and Intricacies of Marketing in China

Small thumbnail

Supply Chain Management and Business Performance

The VASC Model

Small thumbnail

Asymmetric Alliances and Information Systems

Issues and Prospects

Small thumbnail

Optimization in Signal and Image Processing

Edited by Patrick Siarry, University of Paris 12, France

ISBN: 9781848210448

Publication Date: June 2009   Hardback   384 pp.

190.00 USD

Add to cart


Ebook Ebook


This book describes some of the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms and artificial immune systems).


1. Modeling and optimization in image
analysis, Jean Louchet.
2. Artificial evolution and the Parisian approach:
applications in the processing of signals and images,
Pierre Collet, Jean Louchet.
3. Wavelets and fractals for signal and image analysis,
Abdeljalil Ouahabi, Djedjiga Aït Aouit.
4. Information criteria: examples of applications in signal and image
processing, Christian Olivier, Olivier Alata.
5. Quadratic programming and machine learning. Large scale problems and sparsity,
Gaëlle Loosli, Stéphane Canu.
6. Probabilistic modeling of policies and application to optimal sensor management,
Frédéric Dambreville, Francis Celeste, Cécile Simonin.
7. Optimizing emissions for tracking and pursuit of mobile targets, Jean-Pierre Le Cadre.
8. Bayesian inference and Markov models, Christophe Collet.
9. The use of hidden Markov models for image recognition: learning with artificial ants, genetic algorithms and particle swarm optimization,
Sébastien Aupetit, Nicolas Monmarche, Mohamed Slimane.
10. Biological metaheuristics for road sign detection,
Guillaume Dutilleux, Pierre Charbonnier.
11. Metaheuristics for continuous variables. The registration of retinal angiography images,
Johann Dréo, Jean-Claude Nunes, Patrick Siarry.
12. Joint estimation of dynamics and shape of physiological signals
through genetic algorithms, Amine Naït-Ali, Patrick Siarry.
13. Using interactive evolutionary algorithms to help fit cochlear implants, Pierre Collet, Pierrick Legrand,
Claire Bourgeois-Republique, Vincent Pean, Bruno Frachet.

About the Authors

Patrick Siarry is a Professor in automatics and informatics at the University of Paris 12, France.


DownloadTable of Contents - PDF File - 140 Kb

DownloadIntroduction - Sample Chapter - PDF File - 675 Kb

Related Titles

0.04453 s.