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Theory and Applications of Stochastic Processes [electronic resource] : An Analytical Approach / by Zeev Schuss.

By: Contributor(s): Material type: TextTextSeries: Applied Mathematical Sciences ; 170Publisher: New York, NY : Springer New York, 2010Description: XVII, 468 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781441916051
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 519.2 23
LOC classification:
  • QA273.A1-274.9
  • QA274-274.9
Online resources:
Contents:
The Physical Brownian Motion: Diffusion And Noise -- The Probability Space of Brownian Motion -- It#x00F4; Integration and Calculus -- Stochastic Differential Equations -- The Discrete Approach and Boundary Behavior -- The First Passage Time of Diffusions -- Markov Processes and their Diffusion Approximations -- Diffusion Approximations to Langevin#x2019;s Equation -- Large Deviations of Markovian Jump Processes -- Noise-Induced Escape From an Attractor -- Stochastic Stability.
In: Springer eBooksSummary: This book offers an analytical approach to stochastic processes that are most common in the physical and life sciences. Its aim is to make probability theory readily accessible to scientists trained in the traditional methods of applied mathematics, such as integral, ordinary, and partial differential equations and in asymptotic methods, rather than in probability and measure theory. It shows how to derive explicit expressions for quantities of interest by solving equations. Emphasis is put on rational modeling and approximation methods. The book includes many detailed illustrations, applications, examples and exercises. It will appeal to graduate students and researchers in mathematics, physics and engineering.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBook Available
Total holds: 0

The Physical Brownian Motion: Diffusion And Noise -- The Probability Space of Brownian Motion -- It#x00F4; Integration and Calculus -- Stochastic Differential Equations -- The Discrete Approach and Boundary Behavior -- The First Passage Time of Diffusions -- Markov Processes and their Diffusion Approximations -- Diffusion Approximations to Langevin#x2019;s Equation -- Large Deviations of Markovian Jump Processes -- Noise-Induced Escape From an Attractor -- Stochastic Stability.

This book offers an analytical approach to stochastic processes that are most common in the physical and life sciences. Its aim is to make probability theory readily accessible to scientists trained in the traditional methods of applied mathematics, such as integral, ordinary, and partial differential equations and in asymptotic methods, rather than in probability and measure theory. It shows how to derive explicit expressions for quantities of interest by solving equations. Emphasis is put on rational modeling and approximation methods. The book includes many detailed illustrations, applications, examples and exercises. It will appeal to graduate students and researchers in mathematics, physics and engineering.

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