A neural network for the linear complementarity problem
Liao, LZ
AbstractAn artificial neural network is proposed in this paper for solving the linear complementarity problem. The new neural network is based on a reformulation of the linear complementarity problem into the unconstrained minimization problem. Our new neural network can be easily implemented on a circuit. On the theoretical aspect, we analyze the existence of the equilibrium points for our neural network. In addition, we prove that if the equilibrium point exists for the neural network, then any such equilibrium point is both asymptotically and bounded (Lagrange) stable for any initial state. Furthermore, linear programming and certain quadratical programming problems (not necessarily convex) can be also solved by the neural network. Simulation results on several problems including a nonconvex one are also reported. (C) 1999 Elsevier Science Ltd. All rights reserved.
Keywordneural network linear complementarity problem stability
WOS Research AreaComputer Science ; Mathematics
WOS SubjectComputer Science, Interdisciplinary Applications ; Computer Science, Software Engineering ; Mathematics, Applied
WOS IDWOS:000079388600002
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Cited Times:13[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Hong Kong Baptist Univ, Dept Math, Hong Kong, Hong Kong
2.Chinese Acad Sci, Inst Computat Math & Sci Engn Comp, Beijing, Peoples R China
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GB/T 7714
Liao, LZ. A neural network for the linear complementarity problem[J]. MATHEMATICAL AND COMPUTER MODELLING,1999,29(3):9-18.
APA Liao, LZ.(1999).A neural network for the linear complementarity problem.MATHEMATICAL AND COMPUTER MODELLING,29(3),9-18.
MLA Liao, LZ."A neural network for the linear complementarity problem".MATHEMATICAL AND COMPUTER MODELLING 29.3(1999):9-18.
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