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Stochastic Calculus: Applications in Science and Engineering /
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Catalogue Information
Field name
Details
Dewey Class
519.2
Title
Stochastic Calculus ([EBook] :) : Applications in Science and Engineering / / by Mircea Grigoriu.
Author
Grigoriu, Mircea
Other name(s)
SpringerLink (Online service)
Publication
Boston, MA : : Birkhäuser Boston : : Imprint: Birkhäuser, , 2002.
Physical Details
XIV, 775 p. : online resource.
ISBN
9780817682286
Summary Note
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.:
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site
http://dx.doi.org/10.1007/978-0-8176-8228-6
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Subject References:
Applications of Mathematics
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Applied mathematics
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Computational Mathematics and Numerical Analysis
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Computer mathematics
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Engineering mathematics
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Mathematics
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Partial differential equations
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Probabilities
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Probability theory and stochastic processes
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Authors:
Grigoriu, Mircea
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Corporate Authors:
SpringerLink (Online service)
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Classification:
519.2
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