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Introduction to stochastic dynamics / Jinqiao Duan.

By: Material type: TextTextSeries: Cambridge texts in applied mathematicsPublication details: New York : Cambridge University Press, 2015.Description: xvii, 291 pages : illustrations ; 26 cmISBN:
  • 9781107428201
Subject(s): DDC classification:
  • 519.23 23 D812
Contents:
1. Introduction; 2. Background in analysis and probability; 3. Noise; 4. A crash course in stochastic differential equations; 5. Deterministic quantities for stochastic dynamics; 6. Invariant structures for stochastic dynamics; 7. Dynamical systems driven by non-Gaussian Levy motions.
Summary: This book serves as a concise introductory text on stochastic dynamics for applied mathematicians and scientists. Starting from the knowledge base typical for beginning graduate students in applied mathematics, it introduces the basic tools from probability and analysis and then develops for stochastic systems the properties traditionally calculated for deterministic systems. The book's final chapter opens the door to modeling in non-Gaussian situations, typical of many real-world applications. Rich with examples, illustrations, and exercises with solutions, this book is also ideal for self-study.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 519.23 D812 (Browse shelf(Opens below)) Available 137435
Total holds: 0

Includes bibliographical references and index.

1. Introduction;
2. Background in analysis and probability;
3. Noise;
4. A crash course in stochastic differential equations;
5. Deterministic quantities for stochastic dynamics;
6. Invariant structures for stochastic dynamics;
7. Dynamical systems driven by non-Gaussian Levy motions.

This book serves as a concise introductory text on stochastic dynamics for applied mathematicians and scientists. Starting from the knowledge base typical for beginning graduate students in applied mathematics, it introduces the basic tools from probability and analysis and then develops for stochastic systems the properties traditionally calculated for deterministic systems. The book's final chapter opens the door to modeling in non-Gaussian situations, typical of many real-world applications. Rich with examples, illustrations, and exercises with solutions, this book is also ideal for self-study.

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