Theory and Applications of Stochastic Processes

An Analytical Approach

Serie: Applied Mathematical Sciences 170

Stochastic processes and diffusion theory are the mathematical underpinnings of many scientific disciplines, including statistical physics, physical chemistry, molecular biophysics, communications theory and many more. Les mer
Vår pris
1013,-

(Innbundet) Fri frakt!
Leveringstid: Usikker levering*
*Vi bestiller varen fra forlag i utlandet. Dersom varen finnes, sender vi den så snart vi får den til lager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Vår pris: 1013,-

(Innbundet) Fri frakt!
Leveringstid: Usikker levering*
*Vi bestiller varen fra forlag i utlandet. Dersom varen finnes, sender vi den så snart vi får den til lager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Om boka

Stochastic processes and diffusion theory are the mathematical underpinnings of many scientific disciplines, including statistical physics, physical chemistry, molecular biophysics, communications theory and many more. Many books, reviews and research articles have been published on this topic, from the purely mathematical to the most practical.


This book offers an analytical approach to stochastic processes that are most common in the physical and life sciences, as well as in optimal control and in the theory of filltering of signals from noisy measurements. Its aim is to make probability theory in function space readily accessible to scientists trained in the traditional methods of applied mathematics, such as integral, ordinary, and partial differential equations and asymptotic methods, rather than in probability and measure theory.

Fakta

Innholdsfortegnelse

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.