DocumentCode
2188334
Title
On stochastic approximation methods in genetics
Author
Orman, Gabriel V.
Author_Institution
Dept. of Math., Brasov Univ.
fYear
2004
fDate
7-10 June 2004
Firstpage
47
Abstract
As it is known a precise definition of the Brownian motion involves a measure on the path space, such that it is possible to put the Brownian motion on a firm mathematical foundation. In this paper we refer to an application of asymptotic theory of stochastic differential equations in mathematical genetics. The construction of the Brownian motion as a limit of a rescaled random walk can be generalized to a class of Markov chains
Keywords
Brownian motion; Markov processes; binomial distribution; differential equations; genetics; Brownian motion; Markov chain; asymptotic theory; binomial distribution; mathematical genetics; stochastic approximation methods; stochastic differential equation; transition probability; Approximation methods; Atomic measurements; Differential equations; Genetics; Integral equations; Motion measurement; Probability distribution; Stochastic processes; Stochastic resonance; Working environment noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology Interfaces, 2004. 26th International Conference on
Conference_Location
Cavtat
Print_ISBN
953-96769-9-1
Type
conf
Filename
1372373
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