Attractivity Analysis for Recurrent Neural Networks with State-dependent External Input

Gang Baol, Kang Li, Zhenyan Song
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Abstract

This paper introduces a novel kind of discontinu-ous neural networks which are with state-dependent switching external input. The switched external input is defined as a step function with respect to state value. Firstly, we derive a sufficient condition for network state attractivity by dividing the state space according to the swithed external input function and the activation function. At last, one numerical example verifies our results.
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具有状态依赖外部输入的递归神经网络的吸引性分析
本文介绍了一种具有状态依赖切换外部输入的新型不连续神经网络。被切换的外部输入被定义为关于状态值的阶跃函数。首先,根据变换后的外部输入函数和激活函数划分状态空间,得到网络状态吸引的充分条件;最后通过一个数值算例验证了我们的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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