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Introduction to the Theory of Random Processes

N. V. Krylov University of Minnesota, Minneapolis, MN
Available Formats:
Hardcover ISBN: 978-0-8218-2985-1
Product Code: GSM/43
230 pp
List Price: $47.00 MAA Member Price:$42.30
AMS Member Price: $37.60 Electronic ISBN: 978-1-4704-2094-9 Product Code: GSM/43.E 230 pp List Price:$44.00
MAA Member Price: $39.60 AMS Member Price:$35.20
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This product is available for purchase as a bundle. Purchasing as a bundle enables you to save on the electronic version.
List Price: $70.50 MAA Member Price:$63.45
AMS Member Price: $56.40 Click above image for expanded view Introduction to the Theory of Random Processes N. V. Krylov University of Minnesota, Minneapolis, MN Available Formats:  Hardcover ISBN: 978-0-8218-2985-1 Product Code: GSM/43 230 pp  List Price:$47.00 MAA Member Price: $42.30 AMS Member Price:$37.60
 Electronic ISBN: 978-1-4704-2094-9 Product Code: GSM/43.E 230 pp
 List Price: $44.00 MAA Member Price:$39.60 AMS Member Price: $35.20 Bundle Print and Electronic Formats and Save! This product is available for purchase as a bundle. Purchasing as a bundle enables you to save on the electronic version. List Price:$70.50
MAA Member Price: $63.45 AMS Member Price:$56.40
• Book Details

Volume: 432002
MSC: Primary 60;

This book concentrates on some general facts and ideas of the theory of stochastic processes. The topics include the Wiener process, stationary processes, infinitely divisible processes, and Itô stochastic equations.

Basics of discrete time martingales are also presented and then used in one way or another throughout the book. Another common feature of the main body of the book is using stochastic integration with respect to random orthogonal measures. In particular, it is used for spectral representation of trajectories of stationary processes and for proving that Gaussian stationary processes with rational spectral densities are components of solutions to stochastic equations. In the case of infinitely divisible processes, stochastic integration allows for obtaining a representation of trajectories through jump measures. The Itô stochastic integral is also introduced as a particular case of stochastic integrals with respect to random orthogonal measures.

Although it is not possible to cover even a noticeable portion of the topics listed above in a short book, it is hoped that after having followed the material presented here, the reader will have acquired a good understanding of what kind of results are available and what kind of techniques are used to obtain them.

With more than 100 problems included, the book can serve as a text for an introductory course on stochastic processes or for independent study.

Other works by this author published by the AMS include, Lectures on Elliptic and Parabolic Equations in Hölder Spaces and Introduction to the Theory of Diffusion Processes.

Graduate students and research mathematicians, physicists, and engineers interested in the theory of random processes and its applications.

• Chapters
• Chapter 1. Generalities
• Chapter 2. The Wiener process
• Chapter 3. Martingales
• Chapter 4. Stationary processes
• Chapter 5. Infinitely divisible processes
• Chapter 6. Itô stochastic integral
• Reviews

• The book is written in a nice and thorough style. A large number of exercises are contained.

Zentralblatt MATH
• An attractive feature of the book, apart from the nice and meticulous style of writing, is that it contains a large number of examples and exercises (and hints for exercises—some of which are certainly quite ambitious and demanding!).

Mathematical Reviews
• Request Review Copy
• Get Permissions
Volume: 432002
MSC: Primary 60;

This book concentrates on some general facts and ideas of the theory of stochastic processes. The topics include the Wiener process, stationary processes, infinitely divisible processes, and Itô stochastic equations.

Basics of discrete time martingales are also presented and then used in one way or another throughout the book. Another common feature of the main body of the book is using stochastic integration with respect to random orthogonal measures. In particular, it is used for spectral representation of trajectories of stationary processes and for proving that Gaussian stationary processes with rational spectral densities are components of solutions to stochastic equations. In the case of infinitely divisible processes, stochastic integration allows for obtaining a representation of trajectories through jump measures. The Itô stochastic integral is also introduced as a particular case of stochastic integrals with respect to random orthogonal measures.

Although it is not possible to cover even a noticeable portion of the topics listed above in a short book, it is hoped that after having followed the material presented here, the reader will have acquired a good understanding of what kind of results are available and what kind of techniques are used to obtain them.

With more than 100 problems included, the book can serve as a text for an introductory course on stochastic processes or for independent study.

Other works by this author published by the AMS include, Lectures on Elliptic and Parabolic Equations in Hölder Spaces and Introduction to the Theory of Diffusion Processes.

Graduate students and research mathematicians, physicists, and engineers interested in the theory of random processes and its applications.

• Chapters
• Chapter 1. Generalities
• Chapter 2. The Wiener process
• Chapter 3. Martingales
• Chapter 4. Stationary processes
• Chapter 5. Infinitely divisible processes
• Chapter 6. Itô stochastic integral
• The book is written in a nice and thorough style. A large number of exercises are contained.

Zentralblatt MATH
• An attractive feature of the book, apart from the nice and meticulous style of writing, is that it contains a large number of examples and exercises (and hints for exercises—some of which are certainly quite ambitious and demanding!).

Mathematical Reviews
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