Global exponential stability of discrete-time recurrent neural network for solving quadratic programming problems subject to linear constraints

作者：Liu Qingshan; Cao Jinde^*

来源：Neurocomputing, 2011, 74(17): 3494-3501.

DOI：10.1016/j.neucom.2011.06.003

• Discrete-time recurrent neural network
• Globally exponentially stable
• Quadratic programming

In this paper, a discrete-time recurrent neural network with global exponential stability is proposed for solving linear constrained quadratic programming problems. Compared with the existing neural networks for quadratic programming, the proposed neural network in this paper has lower model complexity with only one-layer structure. Moreover, the global exponential stability of the neural network can be guaranteed under some mild conditions. Simulation results with some applications show the performance and characteristic of the proposed neural network.

• 出版日期2011-10
• 单位东南大学