Neural network for solving Nash equilibrium problem in application of multiuser power control

作     者：He, Xing Yu, Junzhi Huang, Tingwen Li, Chuandong Li, Chaojie 

作者机构：Southwest Univ Sch Elect & Informat Engn Chongqing 400715 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Texas A&M Univ Dept Math Doha Qatar RMIT Univ Sch Elect & Comp Engn Melbourne Vic 3001 Australia 

出 版 物：《NEURAL NETWORKS》 (神经网络)

年 卷 期：2014年第57卷

页      面：73-78页

核心收录：

学科分类：1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学] 

基　　金：Fundamental Research Funds for the Central Universities [XDJK2014C118, SWU114007] Natural Science Foundation of China [61374078, 61375102] Qatar National Research Fund [NPRP 4-1162-1-181] 

主　　题：Neural network Multiuser power control Nash game Global convergence 

摘      要：In this paper, based on an equivalent mixed linear complementarity problem, we propose a neural network to solve multiuser power control optimization problems (MPCOP), which is modeled as the noncooperative Nash game in modern digital subscriber line (DSL). If the channel crosstalk coefficients matrix is positive semidefinite, it is shown that the proposed neural network is stable in the sense of Lyapunov and global convergence to a Nash equilibrium, and the Nash equilibrium is unique if the channel crosstalk coefficients matrix is positive definite. Finally, simulation results on two numerical examples show the effectiveness and performance of the proposed neural network. (C) 2014 Elsevier Ltd. All rights reserved.