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Updated: May 28, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
Delay-slope-dependent stability results of recurrent neural networks
Tao Li1, Wei Xing Zheng, Chong Lin
1Department of Information and Communication, Nanjing University of Information Science and Technology, Nanjing 210044, China. litaojia79@yahoo.com.cn
Abstract:
By using the fact that the neuron activation functions are sector bounded and nondecreasing, this brief presents a new method, named the delay-slope-dependent method, for stability analysis of a class of recurrent neural networks with time-varying delays. This method includes more information on the slope of neuron activation functions and fewer matrix variables in the constructed Lyapunov-Krasovskii functional. Then some improved delay-dependent stability criteria with less computational burden and conservatism are obtained. Numerical examples are given to illustrate the effectiveness and the benefits of the proposed method.
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