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【目的】研究一类具有变时滞的模糊Cohen-Grossberg型神经网络在有限时间内的同步。【方法】使用Lyapunov稳定性理论和一些不等式方法,并恰当控制外部输入条件。【结果】得到新的模糊Cohen-Grossberg型神经网络在有限时间内同步的充分条件,且驱动系统和响应系统在有限时间内实现同步。【结论】之前的一些关于神经网络的工作,驱动系统和响应系统是在当时间t→+∞实现同步,相比之下本文结论更加高效实用。
【Objective】 The purpose of this paper is to study the synchronization of a class of fuzzy Cohen-Grossberg neural networks with variable delays in finite time. 【Method】 Lyapunov stability theory and some inequality methods are used, and external input conditions are properly controlled. 【Result】 The sufficient conditions for the new fuzzy Cohen-Grossberg neural network to be synchronized in a finite time are obtained, and the drive system and the response system are synchronized in a finite time. 【Conclusion】 Some previous work on neural network, drive system and response system are synchronized at time t → + ∞, compared with the conclusion of this paper is more efficient and practical.