Maximum-Entropy Networks, Tiziano Squartini; Diego Garlaschelli

Автор: Glenn R. Heidbreder
Название: Maximum Entropy and Bayesian Methods Santa Barbara, California, U.S.A., 1993
ISBN: 0792328515 ISBN-13(EAN): 9780792328513
Издательство: Springer
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Описание: Maximum entropy and Bayesian methods have fundamental, central roles in scientific inference. This volume contains papers presented at the Thirteenth International Workshop on Maximum Entropy and Bayesian Methods. It includes a section, and contributions detailing application in the physical sciences, engineering, law, and economics.

Автор: Guy Jumarie
Название: Maximum Entropy, Information Without Probability and Complex Fractals
ISBN: 9048154677 ISBN-13(EAN): 9789048154678
Издательство: Springer
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Автор: Karmeshu
Название: Entropy Measures, Maximum Entropy Principle and Emerging Applications
ISBN: 3642055311 ISBN-13(EAN): 9783642055317
Издательство: Springer
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Цена: 30039.00 р.
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Описание: The last two decades have witnessed an enormous growth with regard to ap- plications of information theoretic framework in areas of physical, biological, engineering and even social sciences. Claude Shannon in 1948 laid the foundation of the field of information theory in the context of communication theory.

Автор: Kenneth M. Hanson; Richard N. Silver
Название: Maximum Entropy and Bayesian Methods
ISBN: 9401062846 ISBN-13(EAN): 9789401062848
Издательство: Springer
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Описание: Proceedings of the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods, Santa Fe, New Mexico, USA, 1995

Автор: G. Erickson; Joshua T. Rychert; C.R. Smith
Название: Maximum Entropy and Bayesian Methods
ISBN: 0792350472 ISBN-13(EAN): 9780792350477
Издательство: Springer
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Описание: Contains a range of applications of Bayesian statistics and maximum entropy methods to problems of concern in such fields as image processing, coding theory, machine learning, economics, data analysis and other problems. This text is intended for researchers in applied statistics, information theory, coding theory, image and signal processing.

Автор: Guy Jumarie
Название: Maximum Entropy, Information Without Probability and Complex Fractals
ISBN: 0792363302 ISBN-13(EAN): 9780792363309
Издательство: Springer
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Описание: Presents material on three topics, namely the amount of information involved in non-random functions, the amount of information involved in non-probabilistic square matrices (which are not quantum density matrices), and a model of complex-valued fractional Brownian motion of order n defined via random walks in the complex plane.

Автор: G. Erickson; C.R. Smith
Название: Maximum-Entropy and Bayesian Methods in Science and Engineering
ISBN: 9401090564 ISBN-13(EAN): 9789401090568
Издательство: Springer
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Описание: This volume has its origin in the Fifth, Sixth and Seventh Workshops on "Maximum-Entropy and Bayesian Methods in Applied Statistics", held at the University of Wyoming, August 5-8, 1985, and at Seattle University, August 5-8, 1986, and August 4-7, 1987.

Автор: G. Erickson; C.R. Smith
Название: Maximum-Entropy and Bayesian Methods in Science and Engineering
ISBN: 9401078718 ISBN-13(EAN): 9789401078719
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Описание: This volume has its origin in the Fifth, Sixth and Seventh Workshops on and Bayesian Methods in Applied Statistics", held at "Maximum-Entropy the University of Wyoming, August 5-8, 1985, and at Seattle University, August 5-8, 1986, and August 4-7, 1987.

Автор: Nailong Wu
Название: The Maximum Entropy Method
ISBN: 3642644848 ISBN-13(EAN): 9783642644849
Издательство: Springer
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Описание: Forty years ago, in 1957, the Principle of Maximum Entropy was first intro- duced by Jaynes into the field of statistical mechanics. As well as continuing my research in MEM after graduation, I taught a course of the same name at the Graduate School, Chinese Academy of Sciences, Beijingfrom 1987to 1990.

Автор: Wolfgang von der Linden; Volker Dose; Rainer Fisch
Название: Maximum Entropy and Bayesian Methods Garching, Germany 1998
ISBN: 0792357663 ISBN-13(EAN): 9780792357667
Издательство: Springer
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Описание: Taken from the 1998 MaxEnt conference, this work contains a range of applications of Bayesian probability theory and maximum entropy methods to problems of concern in such fields as physics, image processing, coding theory, machine learning, economics, data analysis and various other problems.