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Title
Probability theory and stochastic processes / Pierre Brémaud.
ISBN
9783030401832 (electronic book)
3030401839 (electronic book)
9783030401825
3030401820
Publication Details
Cham : Springer, 2020.
Language
English
Description
1 online resource (717 pages).
Item Number
10.1007/978-3-030-40183-2 doi
Call Number
QA273
Dewey Decimal Classification
519.2
Summary
The ultimate objective of this book is to present a panoramic view of the main stochastic processes which have an impact on applications, with complete proofs and exercises. Random processes play a central role in the applied sciences, including operations research, insurance, finance, biology, physics, computer and communications networks, and signal processing. In order to help the reader to reach a level of technical autonomy sufficient to understand the presented models, this book includes a reasonable dose of probability theory. On the other hand, the study of stochastic processes gives an opportunity to apply the main theoretical results of probability theory beyond classroom examples and in a non-trivial manner that makes this discipline look more attractive to the applications-oriented student. One can distinguish three parts of this book. The first four chapters are about probability theory, Chapters 5 to 8 concern random sequences, or discrete-time stochastic processes, and the rest of the book focuses on stochastic processes and point processes. There is sufficient modularity for the instructor or the self-teaching reader to design a course or a study program adapted to her/his specific needs. This book is in a large measure self-contained.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Description based on print version record.
Series
Universitext.
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.
