Theory and Applications of Stochastic Processes : An Analytical Approach

This book offers an analytical approach to stochastic processes that are most common in the physical and life sciences. Its aim is to make probability theory readily accessible to scientists trained in the traditional methods of applied mathematics, such as integral, ordinary, and partial differenti...

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Detaylı Bibliyografya
Yazar: Schuss, Zeev, 1937-2018
Materyal Türü: Livre numérique
Dil:Anglais
Baskı/Yayın Bilgisi: New York, NY : Springer New York [20..].
Cham : Springer Nature
Edisyon:1st ed. 2010.
Seri Bilgileri:Applied Mathematical Sciences 170
Online Erişim:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Not: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Theory and applications of stochastic processes, an analytical approach, Zeev Schuss, 2009, New York, Springer, 1 vol. (xvii-468 p.), Applied mathematical sciences, 978-1-441-91604-4
• Theory and Applications of Stochastic Processes, Texte imprimé, 9781441916150
• Theory and Applications of Stochastic Processes, Texte imprimé, 9781461425427
• Theory and applications of stochastic processes, an analytical approach, Zeev Schuss, 2009, New York, Springer, 1 vol. (xvii-468 p.), Applied mathematical sciences, 978-1-441-91604-4
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505 1 |a The Physical Brownian Motion: Diffusion And Noise The Probability Space of Brownian Motion It#x00F4; Integration and Calculus Stochastic Differential Equations The Discrete Approach and Boundary Behavior The First Passage Time of Diffusions Markov Processes and their Diffusion Approximations Diffusion Approximations to Langevin#x2019;s Equation Large Deviations of Markovian Jump Processes Noise-Induced Escape From an Attractor Stochastic Stability 
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520 |a This book offers an analytical approach to stochastic processes that are most common in the physical and life sciences. Its aim is to make probability theory readily accessible to scientists trained in the traditional methods of applied mathematics, such as integral, ordinary, and partial differential equations and in asymptotic methods, rather than in probability and measure theory. It shows how to derive explicit expressions for quantities of interest by solving equations. Emphasis is put on rational modeling and approximation methods. The book includes many detailed illustrations, applications, examples and exercises. It will appeal to graduate students and researchers in mathematics, physics and engineering 
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