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A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
Published on: May 25, 2019
A new approach to exponential stability analysis of neural networks with time-varying delays
1Department of Automation, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China. syxu02@yahoo.com.cn
Abstract:
This paper considers the problem of exponential stability analysis of neural networks with time-varying delays. The activation functions are assumed to be globally Lipschitz continuous. A linear matrix inequality (LMI) approach is developed to derive sufficient conditions ensuring the delayed neural network to have a unique equilibrium point, which is globally exponentially stable. The proposed LMI conditions can be checked easily by recently developed algorithms solving LMIs. Examples are provided to demonstrate the reduced conservativeness of the proposed results.
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