National Science Library of Georgia

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Lectures on stochastic analysis : diffusion theory / Daniel W. Stroock.

By: Material type: TextTextSeries: London Mathematical Society student texts ; 6.Publisher: Cambridge : Cambridge University Press, 1987Description: 1 online resource (ix, 128 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780511623752 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 519.2/33 19
LOC classification:
  • QA274.75 .S85 1987
Online resources: Summary: This book is based on a course given at Massachusetts Institute of Technology. It is intended to be a reasonably self-contained introduction to stochastic analytic techniques that can be used in the study of certain problems. The central theme is the theory of diffusions. In order to emphasize the intuitive aspects of probabilistic techniques, diffusion theory is presented as a natural generalization of the flow generated by a vector field. Essential to the development of this idea is the introduction of martingales and the formulation of diffusion theory in terms of martingales. The book will make valuable reading for advanced students in probability theory and analysis and will be welcomed as a concise account of the subject by research workers in these fields.
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Title from publisher's bibliographic system (viewed on 05 Oct 2015).

This book is based on a course given at Massachusetts Institute of Technology. It is intended to be a reasonably self-contained introduction to stochastic analytic techniques that can be used in the study of certain problems. The central theme is the theory of diffusions. In order to emphasize the intuitive aspects of probabilistic techniques, diffusion theory is presented as a natural generalization of the flow generated by a vector field. Essential to the development of this idea is the introduction of martingales and the formulation of diffusion theory in terms of martingales. The book will make valuable reading for advanced students in probability theory and analysis and will be welcomed as a concise account of the subject by research workers in these fields.

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