Title :
Primal neural networks for solving convex quadratic programs
Author :
Xia, Youshen ; Wang, Jun
Author_Institution :
Dept. of Mech. & Autom. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Abstract :
We propose two primal neural networks with globally exponential stability for solving quadratic programming problems. Both the self-feedback and lateral connection matrices in the present network are compared with the Bonzerdoum-Pattison network (1993). Moreover, the size of the proposed networks is same as that of the original problem, smaller than that of primal-dual networks
Keywords :
asymptotic stability; convergence of numerical methods; mathematics computing; matrix algebra; neural nets; quadratic programming; convergence; exponential stability; lateral connection matrices; primal neural networks; quadratic programming; self-feedback; Automation; Electronic mail; Function approximation; Mathematics; Neural network hardware; Neural networks; Neurons; Quadratic programming; Recurrent neural networks; Symmetric matrices;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.831563
