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Stochastic calculus : applications in science and engineering / Mircea Grigoriu.

By: Material type: TextTextPublication details: Boston, MA : Birkhäuser, 2002.Description: xii, 774 p. : ill. ; 24 cmContent type:
Media type:
Carrier type:
ISBN:
  • 9780817642426
  • 9783764342425
  • 0817642420
  • 3764342420
Subject(s): DDC classification:
  • 519.2 21
LOC classification:
  • .G75 2002
Other classification:
  • MAT 606f
  • SK 820
  • SK 850
Online resources:
Contents:
1. Introduction -- 2 Probability Theory -- 3 Stochastic Processes -- 4 Ito's Formula and Stochastic Differential Equations -- 5 Monte Carlo Simulation -- 6 Deterministic Systems and Input -- 7 Deterministic Systems and Stochastic Input -- 8 Stochastic Systems and Deterministic Input -- 9 Stochastic Systems and Input
Summary: The Monte Carlo simulation is used extensively throughout to clarify advanced theoretical concepts and provide solutions to a broad range of stochastic problems." "This self-contained text may be used for several graduate courses and as an important reference resource for applied scientists interested in analytical and numerical methods for solving stochastic problems."--Jacket.Review: "Stochastic problems are defined by algebraic, differential or integral equations with random coefficients and/or input. The type, rather than the particular field of applications, is used to categorize these problems. An introductory chapter defines the types of stochastic problems considered in the book and illustrates some of their applications. Chapter 2-5 outline essentials of probability theory, random processes, stochastic integration, and Monte Carlo simulation. Chapters 6-9 present methods for solving problems defined by equations with deterministic and/or random coefficients and deterministic and/or stochastic inputs.
Holdings
Item type Current library Call number Status Date due Barcode
General Lending Carlow Campus Library General Lending 519.2 (Browse shelf(Opens below)) Available 83764

Includes bibliographical references (p. 757-770) and index.

1. Introduction -- 2 Probability Theory -- 3 Stochastic Processes -- 4 Ito's Formula and Stochastic Differential Equations -- 5 Monte Carlo Simulation -- 6 Deterministic Systems and Input -- 7 Deterministic Systems and Stochastic Input -- 8 Stochastic Systems and Deterministic Input -- 9 Stochastic Systems and Input

The Monte Carlo simulation is used extensively throughout to clarify advanced theoretical concepts and provide solutions to a broad range of stochastic problems." "This self-contained text may be used for several graduate courses and as an important reference resource for applied scientists interested in analytical and numerical methods for solving stochastic problems."--Jacket.

"Stochastic problems are defined by algebraic, differential or integral equations with random coefficients and/or input. The type, rather than the particular field of applications, is used to categorize these problems. An introductory chapter defines the types of stochastic problems considered in the book and illustrates some of their applications. Chapter 2-5 outline essentials of probability theory, random processes, stochastic integration, and Monte Carlo simulation. Chapters 6-9 present methods for solving problems defined by equations with deterministic and/or random coefficients and deterministic and/or stochastic inputs.

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