Mathematical Problems in Engineering
Volume 2010 (2010), Article ID 403749, 13 pages
Research Article

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

College of Science, Yanshan University, Qinhuangdao 066001, China

Received 26 February 2010; Accepted 19 July 2010

Academic Editor: Jitao Sun

Copyright © 2010 Huaiqin Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.