Title :
Solving Quadratic Programming Problems by Delayed Projection Neural Network
Author :
Yongqing Yang ; Jinde Cao
Author_Institution :
Dept. of Math., Southeast Univ., Nanjing
Abstract :
In this letter, the delayed projection neural network for solving convex quadratic programming problems is proposed. The neural network is proved to be globally exponentially stable and can converge to an optimal solution of the optimization problem. Three examples show the effectiveness of the proposed network
Keywords :
neural nets; quadratic programming; convex quadratic programming problems; delayed projection neural network; optimization problem; Artificial neural networks; Delay effects; Design engineering; Equations; Image converters; Lagrangian functions; Mathematics; Neural networks; Quadratic programming; Stability; Convex quadratic programming; delay; neural network; stability; Algorithms; Computer Simulation; Information Storage and Retrieval; Models, Statistical; Neural Networks (Computer); Pattern Recognition, Automated; Programming, Linear; Signal Processing, Computer-Assisted;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2006.880579
