A Novel Recurrent Neural Network for Solving Nonlinear Optimization Problems With Inequality Constraints

This paper presents a novel recurrent neural network for solving nonlinear optimization problems with inequality constraints. Under the condition that the Hessian matrix of the associated Lagrangian function is positive semidefinite, it is shown that the proposed neural network is stable at a Karush

• Type: Journal
• Year: 2008
• Where: TNN
• Authors: Youshen Xia, Gang Feng, Jun Wang
• Keywords: Neural Network, Optimization Problems, Recurrent Neural Network, TNN 2008