Probability Theory and Stochastic Processes

Pierre Brémaud graduated from the École Polytechnique and obtained his Doctorate in Mathematics from the University of Paris VI and his PhD from the department of Electrical Engineering and Computer Science at the University of California, Berkeley. He is a major contributor to the theory of stochastic processes and their applications, and has authored or co-authored several reference books and textbooks on the subject.

“The book is very interesting and useful to a very wide audience: students, postgraduates, practitioners and everybody who wants to study random objects and apply stochastic methods.” (Yuliya S. Mishura, zbMATH 1445.60001, 2020)

• Introduction.-Warming Up.- Integration Theory for Probability.- Probability and Expectation.- Convergence of random sequences.- Markov Chains.- Martingale Sequences.- Ergodic Sequences.- Generalities on Stochastic Processes.- Poisson Processes.- Continuous-Time Markov Chains.- Renewal Theory in Continuous Time.- Brownian Motion.- Wide-sense Stationary Stochastic Processes.- An Introduction to Itô’s Calculus.- Appenndix: Number Theory and Linear Algebra.- Analysis.- Hilbert Spaces.- Z-Transforms.- Proof of Paul Lévy’s Criterion.- Direct Riemann Integrability.- Bibliography.- Index.