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Stochastic Calculus

Applications in Science and Engineering

  • Mircea Grigoriu

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Mircea Grigoriu
    Pages 1-4
  3. Mircea Grigoriu
    Pages 5-101
  4. Mircea Grigoriu
    Pages 103-203
  5. Mircea Grigoriu
    Pages 287-342
  6. Mircea Grigoriu
    Pages 343-427
  7. Mircea Grigoriu
    Pages 429-548
  8. Mircea Grigoriu
    Pages 549-672
  9. Mircea Grigoriu
    Pages 673-756
  10. Back Matter
    Pages 757-774

About this book

Introduction

This work focuses on analyzing and presenting solutions for a wide range of stochastic problems that are encountered in applied mathematics, probability, physics, engineering, finance, and economics. The approach used reduces the gap between the mathematical and engineering literature. Stochastic problems are defined by algebraic, differential or integral equations with random coefficients and/or input. However, it is the type, rather than the particular field of application, that is used to categorize these problems.

An introductory chapter outlines the types of stochastic problems under consideration in this book and illustrates some of their applications. A user friendly, systematic exposition unfolds as follows:  The essentials of probability theory, random processes, stochastic integration, and Monte Carlo simulation are developed in chapters 2--5. The Monte Carlo method is used extensively to illustrate difficult theoretical concepts and solve numerically some of the stochastic problems in chapters 6--9.

Key features:

* Computational skills developed as needed to solve realistic stochastic problems

* Classical mathematical notation used, and essential theoretical facts boxed

* Numerous examples from applied sciences and engineering

* Complete proofs given; if too technical, notes clarify the idea and/or main steps

* Problems at the end of each chapter reinforce applications; hints given.

* Good bibliography at the end of every chapter

* Comprehensive index

This work is unique, self-contained, and far from a collection of facts and formulas. The analytical and numerical methods approach for solving stochastic problems may be used for self-study by a variety of researchers, and in the classroom by first year graduate students.

Keywords

Probability theory Simulation Stochastic calculus applications of mathematics ksa numerical mathematics numerical methods stochastic process stochastic processes

Authors and affiliations

  • Mircea Grigoriu
    • 1
  1. 1.Cornell University School of Civil and Environmental EngineeringIthacaUSA

Bibliographic information

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