Dynamics of a New Hysteresis Memristor CNN

A. Slavova
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引用次数: 1

Abstract

In this paper we study a new class of hysteresis memristor CNN (HM-CNN). The model under investigations contains a simpler state equation with hysteresis operator in the feedback circuit and resonant tunnel diode in the output. The dynamics is studied in different regions depending on hysteresis nonlinearity. The proposed HM-CNN exhibits various complex phenomena in hysteresis region by exploiting its local activity and edge of chaos. Some applications of HM-CNN model in nanostructures are provided.
一种新型迟滞记忆电阻器CNN的动力学研究
本文研究了一类新的磁滞忆阻器CNN (HM-CNN)。所研究的模型包含一个更简单的状态方程,反馈电路中有迟滞算子,输出端有谐振隧道二极管。根据滞回非线性,研究了不同区域的动力学特性。利用局部活动性和混沌边缘,本文提出的hmm - cnn在迟滞区表现出多种复杂现象。给出了神经网络- cnn模型在纳米结构中的一些应用。
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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