A Nonlinear Projection Neural Network for Solving Interval Quadratic Programming Problems and Its Stability Analysis

This paper presents a nonlinear projection neural network for solving interval quadratic programs subject to box-set constraints in engineering applications. Based on the Saddle point theorem, the equilibrium point of the proposed neural network is proved to be equivalent to the optimal solution of...

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Bibliographic Details
Published inMathematical problems in engineering Vol. 2010; no. 2010; pp. 1 - 13
Main Authors He, Lijun, Tao, Feng, Shi, Rui, Wu, Huaiqin, Qin, Leijie
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Puplishing Corporation 2010
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ISSN1024-123X
1563-5147

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Summary:This paper presents a nonlinear projection neural network for solving interval quadratic programs subject to box-set constraints in engineering applications. Based on the Saddle point theorem, the equilibrium point of the proposed neural network is proved to be equivalent to the optimal solution of the interval quadratic optimization problems. By employing Lyapunov function approach, the global exponential stability of the proposed neural network is analyzed. Two illustrative examples are provided to show the feasibility and the efficiency of the proposed method in this paper.
ISSN:1024-123X
1563-5147