A recurrent neural network for solving a class of general variational inequalities

被引：68
|
作者：
Hu, Xiaolin [1 ]
Wang, Jun [1 ]
机构：
[1] Chinese Univ Hong Kong, Dept Automat & Comp Aided Engn, Shatin, Peoples R China
来源：
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS | 2007年 / 37卷 / 03期
关键词：
general projection neural network (GPNN); general variational inequalities (GVIs); global asymptotic stability; global exponential stability; recurrent neural network; FUNCTIONAL-DIFFERENTIAL EQUATIONS; GLOBAL EXPONENTIAL STABILITY; PROJECTED DYNAMICAL-SYSTEMS; RATIO LIMIT THEOREMS; TIME-VARYING DELAYS; OPTIMIZATION PROBLEMS; CONSTRAINED OPTIMIZATION; DESCENT METHODS; CONVERGENCE;
D O I：
10.1109/TSMCB.2006.886166
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a recurrent neural-network model for solving a special class of general variational inequalities (GVIs), which includes classical VIs as special cases. It is proved that the proposed neural network (NN) for solving this class of GVIs can be globally convergent, globally asymptotically stable, and globally exponentially stable under different conditions. The proposed NN can be viewed as a modified version of the general projection NN existing in the literature. Several numerical examples are provided to demonstrate the effectiveness and performance of the proposed NN.
引用
收藏
页码：528 / 539
页数：12
相关论文
共 50 条
  • [1] A Recurrent Neural Network Based on Projection Operator for Extended General Variational Inequalities
    Liu, Qingshan
    Cao, Jinde
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2010, 40 (03): : 928 - 938
  • [2] An inertial projection neural network for solving inverse variational inequalities
    Ju, Xingxing
    Li, Chuandong
    He, Xing
    Feng, Gang
    NEUROCOMPUTING, 2020, 406 : 99 - 105
  • [3] A Delayed Projection Neural Network for Solving Linear Variational Inequalities
    Cheng, Long
    Hou, Zeng-Guang
    Tan, Min
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2009, 20 (06): : 915 - 925
  • [4] A Novel Projection Neural Network for Solving a Class of Monotone Variational Inequalities
    Wen, Xingnan
    Qin, Sitian
    Feng, Jiqiang
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2023, 53 (09): : 5580 - 5590
  • [5] A neural network method for solving a system of linear variational inequalities
    Lan, Heng-you
    Cui, Yi-Shun
    CHAOS SOLITONS & FRACTALS, 2009, 41 (03) : 1245 - 1252
  • [6] A projection neural network with mixed delays for solving linear variational inequality
    Huang, Bonan
    Hui, Guotao
    Gong, Dawei
    Wang, Zhanshan
    Meng, Xiangping
    NEUROCOMPUTING, 2014, 125 : 28 - 32
  • [7] Deep Neural Network Structures Solving Variational Inequalities
    Combettes, Patrick L.
    Pesquet, Jean-Christophe
    SET-VALUED AND VARIATIONAL ANALYSIS, 2020, 28 (03) : 491 - 518
  • [8] Solving generally constrained generalized linear variational inequalities using the general projection neural networks
    Hu, Xiaolin
    Wang, Jun
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2007, 18 (06): : 1697 - 1708
  • [9] DOUBLE PROJECTION NEURAL NETWORK MODEL FOR SOLVING PSEUDOMONOTONE VARIATIONAL INEQUALITIES
    Malek, A.
    Ezazipour, S.
    Hosseinipour-Mahani, N.
    FIXED POINT THEORY, 2011, 12 (02): : 401 - 418
  • [10] Algorithm for solving a new class of general mixed variational inequalities in Banach spaces
    Xia, Fu-Quan
    Huang, Nan-Jing
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2008, 220 (1-2) : 632 - 642
12345