A dual neural network for convex quadratic programming subject to linear equality and inequality constraints

Physics Letters, Section A: General, Atomic and Solid State Physics

Volumn 298, Issue 4, 2002, Pages 271-278

  Zhang, Yunong ^a   Wang, Jun ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Dual neural network; Global convergence; Linear constraint; Projection operator; Quadratic programming

Indexed keywords

CONSTRAINT THEORY; NETWORK ARCHITECTURE; NONLINEAR EQUATIONS; PIECEWISE LINEAR TECHNIQUES; QUADRATIC PROGRAMMING;

BOUND CONSTRAINTS; CONVEX QUADRATIC PROGRAMMING; DUAL NEURAL NETWORKS; GLOBAL CONVER-GENCE; INEQUALITY CONSTRAINT; LINEAR CONSTRAINTS; PROJECTION OPERATOR; QUADRATIC PROGRAMMING PROBLEMS;

RECURRENT NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CALCULATION; MODEL; PHYSICS; PROBLEM SOLVING;

EID: 17944387843     PISSN: 03759601     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0375-9601(02)00424-3     Document Type: Article

References (22)

1. Recurrent neural networks for optimization: The state of art