On stochastic approximation methods in genetics

被引：0
|
作者：
Orman, GV [1 ]
机构：
[1] Transilvania Univ Brasov, Dept Math, Brasov 2200, Romania
来源：
ITI 2004: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY INTERFACES | 2004年
关键词：
Brownian motion; stochastic differential equation; Markov chain; transition probability; binomial distribution;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：47 / 52
页数：6
相关论文
共 50 条
  • [1] METHODS OF STOCHASTIC APPROXIMATION
    LOGINOV, NV
    AUTOMATION AND REMOTE CONTROL, 1966, 27 (04) : 707 - &
  • [2] METHODS OF STOCHASTIC APPROXIMATION - INTRODUCTION
    TSYPKIN, YZ
    AUTOMATION AND REMOTE CONTROL, 1966, 27 (04) : 706 - &
  • [3] ON THE METHODS OF STOCHASTIC-APPROXIMATION
    ALBER, JI
    SHILMAN, SV
    DOKLADY AKADEMII NAUK SSSR, 1980, 255 (02): : 265 - 269
  • [4] ON STOCHASTIC-APPROXIMATION METHODS
    WOLFOWITZ, J
    ANNALS OF MATHEMATICAL STATISTICS, 1956, 27 (04): : 1151 - 1156
  • [5] MULTIDIMENSIONAL STOCHASTIC APPROXIMATION METHODS
    BLUM, JR
    ANNALS OF MATHEMATICAL STATISTICS, 1954, 25 (04): : 737 - 744
  • [6] Combining the Stochastic Counterpart and Stochastic Approximation Methods
    Jean-Pierre Dussault
    Donald Labrecque
    Pierre L'Ecuyer
    Reuven Y. Rubinstein
    Discrete Event Dynamic Systems, 1997, 7 : 5 - 28
  • [7] Combining the stochastic counterpart and stochastic approximation methods
    Dussault, JP
    Labrecque, D
    LEcuyer, P
    Rubinstein, RY
    DISCRETE EVENT DYNAMIC SYSTEMS-THEORY AND APPLICATIONS, 1997, 7 (01): : 5 - 28
  • [8] PENALTY METHODS WITH STOCHASTIC APPROXIMATION FOR STOCHASTIC NONLINEAR PROGRAMMING
    Wang, Xiao
    Ma, Shiqian
    Yuan, Ya-Xiang
    MATHEMATICS OF COMPUTATION, 2017, 86 (306) : 1793 - 1820
  • [9] Random directions methods in stochastic approximation
    Kushner, HJ
    Yin, G
    PROCEEDINGS OF THE 36TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-5, 1997, : 3430 - 3435
  • [10] ON CHOICE OF DESIGN IN STOCHASTIC APPROXIMATION METHODS
    FABIAN, V
    ANNALS OF MATHEMATICAL STATISTICS, 1968, 39 (02): : 457 - &
12345