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Neural Computation
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The Projection Neural Network for Solving Convex Nonlinear Programming
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A neural network for solving a convex quadratic bilevel programming problem
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IEEE Transactions on Neural Networks
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Journal of Computational and Applied Mathematics
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The neural network for solving convex nonlinear programming problem
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
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In this paper, we present a neural network for solving the nonlinear convex programming problem in real time by means of the projection method. The main idea is to convert the convex programming problem into a variational inequality problem. Then a dynamical system and a convex energy function are constructed for resulting variational inequality problem. It is shown that the proposed neural network is stable in the sense of Lyapunov and can converge to an exact optimal solution of the original problem. Compared with the existing neural networks for solving the nonlinear convex programming problem, the proposed neural network has no Lipschitz condition, no adjustable parameter, and its structure is simple. The validity and transient behavior of the proposed neural network are demonstrated by some simulation results.