
Preface  Preview Material  Table of Contents  Supplementary Material 
Courant Lecture Notes 2007; 126 pp; softcover Volume: 16 ISBN10: 0821840851 ISBN13: 9780821840856 List Price: US$32 Member Price: US$25.60 Order Code: CLN/16 See also: Malliavin Calculus and Its Applications  David Nualart Random Walk Intersections: Large Deviations and Related Topics  Xia Chen  This is a brief introduction to stochastic processes studying certain elementary continuoustime processes. After a description of the Poisson process and related processes with independent increments as well as a brief look at Markov processes with a finite number of jumps, the author proceeds to introduce Brownian motion and to develop stochastic integrals and Itô's theory in the context of onedimensional diffusion processes. The book ends with a brief survey of the general theory of Markov processes. The book is based on courses given by the author at the Courant Institute and can be used as a sequel to the author's successful book Probability Theory in this series. Srinivasa S. R. Varadhan is the winner of the 2007 Abel Prize. Varadhan was awarded the prize "for his fundamental contributions to probability theory and in particular for creating a unified theory of large deviations". Read more here. Titles in this series are copublished with the Courant Institute of Mathematical Sciences at New York University. Readership Graduate students and research mathematicians interested in stochastic processes. Reviews "The text is one of those that may be strongly recommended to all young mathematicians as a starter to precede a deeper study of probability and stochastic processes."  EMS Newsletter "Amazingly, almost all of the proofs are given explicitly. In fact the author provides only eight references in the bibliography. This reflects the fact that, as a whole, this book is written in a totally selfcontained manner. ...I can say that this book is a set of very wellwritten lecture notes, and it is organized as a clear synthesis of the theory of continuoustime stochastic processes with many examples and with plenty of exercises..."  Mathematical Reviews 


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