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A dynamic system model for solving convex nonlinear optimization problems. (English) Zbl 1250.90067
Summary: This paper proposes a feedback neural network model for solving convex nonlinear programming (CNLP) problems. Under the condition that the objective function is convex and all constraint functions are strictly convex or that the objective function is strictly convex and the constraint function is convex, the proposed neural network is proved to be stable in the sense of Lyapunov and globally convergent to an exact optimal solution of the original problem. The validity and transient behavior of the neural network are demonstrated by using some examples.

MSC:
90C25 Convex programming
37N40 Dynamical systems in optimization and economics
92B20 Neural networks for/in biological studies, artificial life and related topics
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