Engineers daily encounter technological problems of growing complexity which occur in very diverse fields, such as telecommunication, genomics ad biomedical engineering. The problem to be solved can often be expressed in the form of an optimization problem: an objective function is defined, one that seeks to minimize vis-a-vis all parameters concerned. 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; metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms and artificial immune systems).
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Patrick Siarry was born in France in 1952. He received the PhD degree from the University Paris 6, in 1986 and the Doctorate of Science (Habilitation) from the University Paris 11, in 1994. He was first involved in the development of analog and digital models of nuclear power plants at Electricite de France. Since 1995 he is a full professor in automatics and informatics. His main research interests are the improvement of optimization "metaheuristics" and their application to various engineering fields.
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