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Engineering Mathematics II Algebraic Stochastic And Analy

 
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MessagePosté le: Jeu 6 Juil 2017 - 04:22    Sujet du message: Engineering Mathematics II Algebraic Stochastic And Analy Répondre en citant




This book highlights the latest advances in engineering mathematics with a main focus on the mathematical models, structures, concepts, problems and computational methods and algorithms most relevant for applications in modern technologies and engineering. It addresses mathematical methods of algebra, applied matrix analysis, operator analysis, probability theory and stochastic processes, geometry and computational methods in network analysis, data classification, ranking and optimisation.

The individual chapters cover both theory and applications, and include a wealth of figures, schemes, algorithms, tables and results of data analysis and simulation. Presenting new methods and results, reviews of cutting-edge research, and open problems for future research, they equip readers to develop new mathematical methods and concepts of their own, and to further compare and analyse the methods and results discussed.

The book consists of contributed chapters covering research developed as a result of a focused international seminar series on mathematics and applied mathematics and a series of three focused international research workshops on engineering mathematics organised by the Research Environment in Mathematics and Applied Mathematics at Mälardalen University from autumn 2014 to autumn 2015: the International Workshop on Engineering Mathematics for Electromagnetics and Health Technology; the International Workshop on Engineering Mathematics, Algebra, Analysis and Electromagnetics; and the 1st Swedish-Estonian International Workshop on Engineering Mathematics, Algebra, Analysis and Applications.

It serves as a source of inspiration for a broad spectrum of researchers and research students in applied mathematics, as well as in the areas of applications of mathematics considered in the book.



Details:
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price: $115.46
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publisher: Springer; 1st ed. 2016 edition (March 11, 2017)
lang: English
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isbn: 3319421042, 978-3319421049,
weight: 1.8 pounds (
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Engineering Mathematics II: Algebraic, Stochastic and Analysis Structures for Networks, Data Classification and Optimization (Springer Proceedings in Mathematics & Statistics) Sergei Silvestrov
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"Unsupervised Learning of Image Manifolds by Semidefinite Programming"It addresses mathematical methods of algebra, applied matrix analysis, operator analysis, probability theory and stochastic processes, geometry and computational methods in network analysis, data classification, ranking and optimisationScience, 290:2319-2323JMirror Descent and Nonlinear Projected Subgradient Methods for Convex Optimization, Operations Research Letters, 31, (2003), 167-175 [Seminar] Big Data and Deep Machine Learning Professor Tong Zhang, Rutgers University and Baidu IncUser Name: Password: Remember me on this computer Cancel Forgot your password? [LLE] Roweis, Sam T

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