期刊文献+

Stochastic Approximation Method for Fixed Point Problems 被引量:1

Stochastic Approximation Method for Fixed Point Problems
下载PDF
导出
摘要 We study iterative processes of stochastic approximation for finding fixed points of weakly contractive and nonexpansive operators in Hilbert spaces under the condition that operators are given with random errors. We prove mean square convergence and convergence almost sure (a.s.) of iterative approximations and establish both asymptotic and nonasymptotic estimates of the convergence rate in degenerate and non-degenerate cases. Previously the stochastic approximation algorithms were studied mainly for optimization problems. We study iterative processes of stochastic approximation for finding fixed points of weakly contractive and nonexpansive operators in Hilbert spaces under the condition that operators are given with random errors. We prove mean square convergence and convergence almost sure (a.s.) of iterative approximations and establish both asymptotic and nonasymptotic estimates of the convergence rate in degenerate and non-degenerate cases. Previously the stochastic approximation algorithms were studied mainly for optimization problems.
出处 《Applied Mathematics》 2012年第12期2123-2132,共10页 应用数学(英文)
关键词 HILBERT Spaces STOCHASTIC Approximation Algorithm Weakly Contractive OPERATORS NONEXPANSIVE OPERATORS Fixed Points CONVERGENCE in Mean Square CONVERGENCE ALMOST Sure (a.s.) Nonasymptotic Estimates of CONVERGENCE Rate Hilbert Spaces Stochastic Approximation Algorithm Weakly Contractive Operators Nonexpansive Operators Fixed Points Convergence in Mean Square Convergence Almost Sure (a.s.) Nonasymptotic Estimates of Convergence Rate
  • 相关文献

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部