TY - JOUR
T1 - A neural network for a class of convex quadratic minimax problems with constraints
AU - Gao, Xing-Bao
AU - Liao, Li-Zhi
AU - Xue, Weimin
N1 - Funding Information:
Manuscript received October 26, 2001; revised July 23, 2002 and October 23, 2002. This work was supported in part by Grants FRG/99-00/II-23 and FRG/00-01/II-63 of Hong Kong Baptist University and HKBU2059/02P from the Research Grant Council of Hong Kong. X.-B. Gao is with the Department of Mathematics, Shaanxi Normal University, Xi’an, Shaanxi 710062, P. R. China. L.-Z. Liao and W. Xue are with the Department of Mathematics, Hong Kong Baptist University Kowloon Tong, Hong Kong, P.R. China (e-mail: [email protected]; [email protected]). The corresponding author is L.-Z. Liao, Digital Object Identifier 10.1109/TNN.2004.824405
PY - 2004/5
Y1 - 2004/5
N2 - In this paper, we propose a neural network for solving a class of convex quadratic minimax problems with constraints. Four sufficient conditions are provided to ensure the asymptotic stability of the proposed network. Furthermore, the exponential stability of the proposing network is also proved under certain conditions. The results obtained here can be further extended to the globally projected dynamical system. In addition, some new stability conditions for the system are also obtained. Since our stability conditions can be easily checked in practice, these results becomes more attractive in real applications.
AB - In this paper, we propose a neural network for solving a class of convex quadratic minimax problems with constraints. Four sufficient conditions are provided to ensure the asymptotic stability of the proposed network. Furthermore, the exponential stability of the proposing network is also proved under certain conditions. The results obtained here can be further extended to the globally projected dynamical system. In addition, some new stability conditions for the system are also obtained. Since our stability conditions can be easily checked in practice, these results becomes more attractive in real applications.
KW - Convergence and stability
KW - Minimax problem
KW - Neural network
KW - Saddle point
UR - http://www.scopus.com/inward/record.url?scp=2542622863&partnerID=8YFLogxK
U2 - 10.1109/TNN.2004.824405
DO - 10.1109/TNN.2004.824405
M3 - Journal article
C2 - 15384550
AN - SCOPUS:2542622863
SN - 1045-9227
VL - 15
SP - 622
EP - 628
JO - IEEE Transactions on Neural Networks
JF - IEEE Transactions on Neural Networks
IS - 3
ER -