A new delayed projection neural network for solving quadratic programming problems

In this paper, a new delayed projection neural network with mixed delays is proposed for solving a class of quadratic programming (QP) problems. By the Lyapunov-Krasovskii theory and the linear matrix inequality (LMI) method, the proposed neural network is proved to be convergent to the optimal solu...

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Bibliographic Details
Main Authors: Bonan Huang, Huaguang Zhang, Zhanshan Wang, Meng Dong
Format: Conference Proceeding
Language:English
Online Access:Request full text
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Summary:In this paper, a new delayed projection neural network with mixed delays is proposed for solving a class of quadratic programming (QP) problems. By the Lyapunov-Krasovskii theory and the linear matrix inequality (LMI) method, the proposed neural network is proved to be convergent to the optimal solution of the QP problems exponentially. The validity of the proposed neural network is verified by two simulation examples.
ISSN:2161-4393
2161-4407
DOI:10.1109/IJCNN.2010.5596930