Stochastic Processes in Science Engineering and Finance 1st Edition by Frank Beichelt ISBN 1584884932 978-1584884934

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Product details: 

ISBN 10: 1584884932

ISBN 13:  978-1584884934

Author: Frank Beichelt 
This book presents a self-contained introduction to stochastic processes with emphasis on their applications in science, engineering, finance, computer science, and operations research. It provides theoretical foundations for modeling time-dependent random phenomena in these areas and illustrates their application by analyzing numerous practical examples.

The treatment assumes few prerequisites, requiring only the standard mathematical maturity acquired by undergraduate applied science students. It includes an introductory chapter that summarizes the basic probability theory needed as background. Numerous exercises reinforce the concepts and techniques discussed and allow readers to assess their grasp of the subject. Solutions to most of the exercises are provided in an appendix. While focused primarily on practical aspects, the presentation includes some important proofs along with more challenging examples and exercises for those more theoretically inclined.

Mastering the contents of this book prepares readers to apply stochastic modeling in their own fields and enables them to work more creatively with software designed for dealing with the data analysis aspects of stochastic processes.

Table of contents: 

Chapter 1 – Random Events and Their Probabilities

• 1.1 Random Events and Their Probabilities

• Abstract

Chapter 2 – Motivation and Terminology

• 2.1 Motivation and Terminology

• Abstract

Chapter 3 – Basic Concepts

• 3.1 Basic Concepts

• Abstract

Chapter 4 – Foundations and Examples

• 4.1 Foundations and Examples

• Abstract

Chapter 5 – Basic Concepts and Examples

• 5.1 Basic Concepts and Examples

• Abstract

Chapter 6 – Discrete-Time Martingales

• 6.1 Discrete-Time Martingales

  • 6.1.1 Definition and Examples

• Abstract

Chapter 7 – Introduction

• 7.1 Introduction

• Abstract

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Tags: Frank Beichelt, Stochastic Processes, Engineering and Finance