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A New One-Layer Neural Network for Linear and Quadratic Programming

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2 Author(s)
Xingbao Gao ; Coll. of Math. & Inf. Sci., Shaanxi Normal Univ., Xi''an, China ; Li-Zhi Liao

In this paper, we present a new neural network for solving linear and quadratic programming problems in real time by introducing some new vectors. The proposed neural network is stable in the sense of Lyapunov and can converge to an exact optimal solution of the original problem when the objective function is convex on the set defined by equality constraints. Compared with existing one-layer neural networks for quadratic programming problems, the proposed neural network has the least neurons and requires weak stability conditions. The validity and transient behavior of the proposed neural network are demonstrated by some simulation results.

Published in:

Neural Networks, IEEE Transactions on  (Volume:21 ,  Issue: 6 )

Date of Publication:

June 2010

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