Cellular neural network with hybrid single-electron and MOS transistors architecture and its application
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Published:2009
Issue:6
Volume:58
Page:4183
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ISSN:1000-3290
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Container-title:Acta Physica Sinica
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language:
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Short-container-title:Acta Phys. Sin.
Author:
Li Qin ,Cai Li ,Feng Chao-Wen ,
Abstract
Based on both the cell equivalent circuit of cellular neural network and the electrical characteristic model of cellular neural networks(CNN) cell,the cell circuit of cellular neural networks is implemented. The activation function of cell circuit is made of two cascaded SET-MOS inverter, which is proposed previously by the author. The CNN cloning template is built by coupling capacitance of input terminal. Then the CNN and its application in image processing are built and studied. The computer simulation results show that the designed circuits is suitable for CNN implementation because of its simple structure, low power dissipation and fast response. The designed circuit can be used to form CNN of various scales so as to further satisfy the need of large-scale signal processing and improve the density of integrated circuit.
Publisher
Acta Physica Sinica, Chinese Physical Society and Institute of Physics, Chinese Academy of Sciences
Subject
General Physics and Astronomy
Cited by
1 articles.
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