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Convergence analysis of discrete-time simplified dual neural network for solving convex quadratic programming problems

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4 Author(s)
Lu Yang ; Department of Automation, Shanghai Jiao Tong University; Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai 200240 ; Li Dewei ; Xi Yugeng ; Lu Jianbo

The convergence property of discrete-time simplified dual neural network for convex quadratic programming is investigated. By choosing a proper Lyapunov function, a sufficient condition for global convergence is obtained. The convergence rate under the condition is also analyzed, and the exponential convergence property under the condition is proved. Simulation verifies the validity of the theoretical results obtained in this paper.

Published in:

Control Conference (CCC), 2012 31st Chinese

Date of Conference:

25-27 July 2012