Linear Simultaneous Equations’ Neural Solution and Its Application to Convex Quadratic Programming with Equality‐Constraint

Yuhuan Chen, Chenfu Yi and Jian Zhong

Journal of Applied Mathematics, 2013, vol. 2013, issue 1

Abstract: A gradient‐based neural network (GNN) is improved and presented for the linear algebraic equation solving. Then, such a GNN model is used for the online solution of the convex quadratic programming (QP) with equality‐constraints under the usage of Lagrangian function and Karush‐Kuhn‐Tucker (KKT) condition. According to the electronic architecture of such a GNN, it is known that the performance of the presented GNN could be enhanced by adopting different activation function arrays and/or design parameters. Computer simulation results substantiate that such a GNN could obtain the accurate solution of the QP problem with an effective manner.

Date: 2013
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https://doi.org/10.1155/2013/695647

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2013:y:2013:i:1:n:695647

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