Optimisation in Signal and Image Processing

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Patrick Siarry
Wiley, Jan 5, 2010 - Technology & Engineering - 352 pages
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This book describes 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).

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About the author (2010)

Rajiv J. Kapadia is the director of the Honors program and a Professor in the Electrical Engineering Department at Minnesota State University in Mankato, USA. He obtained his academic degrees from The University of Bombay and from the University of Oklahoma. Dr. Kapadia is experienced in teaching in several different university systems as he has taught in the University of Queensland in Brisbane, Australia, and in the University of Mumbai, India. He spent most of his career teaching and consulting. Professor Kapadia has authored several scientific publications as well as two text books.

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