The book is an introduction to modern probability theory written by one of the famous experts in this area.

In this volume the general theory of discrete-parameter (time) controlled processes (Chapter 1) and those with continuous-time (Chapter 2), as well as the theory of controlled stochastic differential equations (Chapter 3), are presented.

Covers measure theory, axiomatization of probability theory, processes with independent increments, Markov processes and limit theorems for random processes, more. A wealth of results, ideas, and techniques distinguish this text.

Three-part treatment introduces basics plus theory of stochastic differential equations and various limit theorems connected with convergence of sequence of Markov chains to Markov process with continuous time. 1965 edition.