Convergence analysis of discrete time recurrent neural networks for linear variational inequality problem

Proceedings of the International Joint Conference on Neural Networks

Volumn 3, Issue , 2002, Pages 2470-2475

  Tang, H J ^a   Tan, K C ^a   Zhang, Y ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; LINEAR EQUATIONS; MATHEMATICAL MODELS; MATRIX ALGEBRA; NUMERICAL ANALYSIS; PROBLEM SOLVING; VARIATIONAL TECHNIQUES;

LINEAR VARIATIONAL INEQUALITY PROBLEM; POSITIVE DEFINITE MATRIX;

RECURRENT NEURAL NETWORKS;

EID: 0036083004     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. Neural network for quadratic optimization with bound constraints
2. New conditions for global stability of neural networks with applications to linear and quadratic programming problems
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4. Neural networks for nonlinear programming
5. A recurrent neural network for nonlinear optimization with a continuously differentiable objective function and bound constraints
6. Linear and quadratic programming nerual network analysis
7. Convergence analysis of a discrete-time recurrent neural networks to perform quadratic real optimization with bound constraints
8. Simple neural optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit