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Updated: May 1, 2026

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
Published on: May 25, 2019
Stability and synchronization for discrete-time complex-valued neural networks with time-varying delays
Hao Zhang1, Xing-yuan Wang1, Xiao-hui Lin1
1Faculty of Electronic Information & Electrical Engineering, Dalian University of Technology, Dalian, China.
Abstract:
In this paper, the synchronization problem for a class of discrete-time complex-valued neural networks with time-varying delays is investigated. Compared with the previous work, the time delay and parameters are assumed to be time-varying. By separating the real part and imaginary part, the discrete-time model of complex-valued neural networks is derived. Moreover, by using the complex-valued Lyapunov-Krasovskii functional method and linear matrix inequality as tools, sufficient conditions of the synchronization stability are obtained. In numerical simulation, examples are presented to show the effectiveness of our method.
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