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Dynamical behaviors of Hopfield neural network with multilevel activation functions

机译:具有多级激活函数的Hopfield神经网络的动力学行为

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摘要

When the activation function possesses multilevel property, the Hopfield neural network has some novel dynamical behaviors, and it is worthwhile to study. First, some properties about the activation function are obtained, on this foundation, some theoretical analysis about the quasi-equilibrium points has been made. From local and global view, some theorems about the boundedness are presented. Finally, two theorems about the first derivative of trajectory with respect to time are found, the first theorem indicates that the trajectory cannot keep increasing or decreasing for time t > t(0), the second theorem is about the complete stability of the trajectory. (c) 2005 Elsevier Ltd. All rights reserved.
机译:当激活函数具有多级性质时,Hopfield神经网络具有一些新颖的动力学行为,值得研究。首先,获得了有关激活函数的一些性质,在此基础上,对准平衡点进行了一些理论分析。从局部和全局角度,提出了关于有界性的一些定理。最后,找到关于时间的轨迹一阶导数的两个定理,第一个定理表明在时间t> t(0)时轨迹不能保持递增或递减,第二个定理是关于轨迹的完全稳定性。 (c)2005 Elsevier Ltd.保留所有权利。

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