A strong approximation theorem for stochastic recursive algorithms

被引：13

作者：

Borkar, VS ^{[1
]}

Mitter, SK

机构：

[1] Indian Inst Sci, Dept Comp Sci & Automat, Bangalore 560012, Karnataka, India

[2] MIT, Informat & Decis Syst Lab, Cambridge, MA 02139 USA

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 1999年 / 100卷 / 03期

关键词：

stochastic algorithms; approximation of stochastic differential equations; constant stepsize algorithms; asymptotic behavior;

D O I：

10.1023/A:1022630321574

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

The constant stepsize analog of Gelfand-Mitter type discrete-time stochastic recursive algorithms is shown to track an associated stochastic differential equation in the strong sense, i.e., with respect to an appropriate divergence measure.

引用

页码：499 / 513

页数：15

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