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Dan . Ed(S): Crisan - Stochastic Analysis - 9783642422843 - V9783642422843
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Stochastic Analysis

€ 127.85
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Description for Stochastic Analysis Paperback. Stochastic Analysis provides mathematical tools to both describe and model high dimensional random systems. The text presents a sample of the current research in the different branches of the subject, including collected works of the participants at the the 7th ISAAC Congress at Imperial College London, July 2009. Editor(s): Crisan, Dan. Num Pages: 307 pages, biography. BIC Classification: PBT. Category: (G) General (US: Trade). Dimension: 235 x 155 x 17. Weight in Grams: 474.

Stochastic Analysis aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume “Stochastic Analysis 2010” provides a sample of the current research in the different branches of the subject. It includes the collected works of the participants at the Stochastic Analysis section ... Read more

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Product Details

Format
Paperback
Publication date
2014
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
307
Condition
New
Number of Pages
299
Place of Publication
Berlin, Germany
ISBN
9783642422843
SKU
V9783642422843
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Dan . Ed(S): Crisan
Dr. Dan Crisan is a Reader in Mathematics at Imperial College London, whose expertise area lies in Stochastic Analysis with applications in Engineering and Finance. His main area of research is stochastic filtering theory, a topic which deals with the estimation of partially observed signals. Some of the many applications of stochastic filtering are ... Read more

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