An Over-Relaxed (A,η,m)-Proximal Point Algorithm for System of Nonlinear Fuzzy-Set Valued Operator Equation Frameworks and Fixed Point Problems

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• 作者：Heng-you Lan (1)
  Xiao Wang (2)
  Tingjian Xiong (1)
  Yumin Xiang (1)
• 关键词：(A ; η ; m) ; maximal monotonicity – nonlinear fuzzy ; set valued operator equation and fixed point problem – Over ; relaxed (A ; η ; m) ; proximal Point Algorithm with errors – variational graphical convergence
• 刊名：Lecture Notes in Computer Science
• 出版年：2011
• 出版时间：2011
• 年：2011
• 卷：7027
• 期：1
• 页码：133-142
• 全文大小：207.5 KB
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  13. Lan, H.Y.: Approximation solvability of nonlinear random (A,η)-resolvent operator equations with random relaxed cocoercive operators. Comput. Math. Appl. 57(4), 624–632 (2009)
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• 作者单位：1. School of Science, Sichuan University of Science & Engineering, Zigong, Sichuan 643000, P.R. China2. School of Computer and Science, Sichuan University of Science & Engineering, Zigong, Sichuan 643000, P.R. China
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

In order to find the common solutions for nonlinear fuzzy-set valued operator equations and fixed point problems of Lipschitz continuous operators in Hilbert spaces, the purpose of this paper is to construct a new class of over-relaxed (A,η,m)-proximal point algorithm framework with errors by using some results on the resolvent operator corresponding to (A, η, m)-maximal monotonicity. Further, the variational graph convergence analysis for this algorithm framework is investigated. Finally, some examples of applying the main result is also given. The results presented in this paper improve and generalize some well known results in recent literatures.