Lectures on Stochastic Processes
by K. Ito
Publisher: Tata Institute of Fundamental Research 1960
Number of pages: 207
In this course of lectures the author discusses the elementary parts of Stochastic Processes from the view point of Markov Processes. Topics covered: Markov Processes; Srong Markov Processes; Multi-dimensional Brownian Motion; Additive Processes; Stochastic Differential Equations; Linear Diffusion.
Download or read it online for free here:
by Matt Scott - University of Waterloo
This book is designed as an introduction to the ideas and methods used to formulate mathematical models of physical processes in terms of random functions. A senior undergraduate course offered to students with a suitably mathematical background.
by I. F. Wilde
A gentle introduction to the mathematics of Stochastic Analysis. From the table of contents: Introduction; Conditional expectation; Martingales; Stochastic integration - informally; Wiener process; Ito's formula; Bibliography.
by S.P. Meyn, R.L. Tweedie - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.
by S. Watanabe - Tata Institute of Fundamental Research
The author's main purpose in these lectures was to study solutions of stochastic differential equations as Wiener functionals and apply to them some infinite dimensional functional analysis. This idea was due to P. Malliavin.