A Projection Neural Network with Time Delays for Solving Linear Variational Inequality Problems and Its Applications Academic Article

abstract

• 2015, Springer Science+Business Media New York. In this paper, a new projection neural network with discrete and distributed delays is presented for solving linear variational inequality problems. Some novel sufficient conditions ensuring globally exponential stability are derived by employing matrix measure and differential inequality technique, and the easily checkable conditions are less restrictive. Furthermore, based on the Lagrange multiplier, the proposed neural network can solve the quadratic programming problems. Finally, some simulation results with applications to finance and image fusion are given to demonstrate the effective performance of the neural network.

authors

• Huang, Tingwen

published proceedings

• CIRCUITS SYSTEMS AND SIGNAL PROCESSING

author list (cited authors)

• Sha, C., Zhao, H., Huang, T., & Hu, W.

citation count

• 5

complete list of authors

• Sha, Chunlin||Zhao, Hongyong||Huang, Tingwen||Hu, Wen

publication date

• August 2016

publisher

• Springer Nature  Publisher

published in

• Circuits, Systems and Signal Processing  Journal

keywords

• Discrete Delays
• Distributed Delays
• Globally Exponential Stability
• Image Fusion
• Linear Variational Inequality
• Projection Neural Network

Digital Object Identifier (DOI)

• 10.1007/s00034-015-0176-4

start page

• 2789

end page

• 2809

volume

• 35

issue

• 8

URL

• http://dx.doi.org/10.1007/s00034-015-0176-4

user-defined tag

• 10 Reduced Inequalities