Open AccessCellular neural network with hybrid single-electron and MOS transistors architecture and its application
Author(s) -
Li Q,
Cai Li,
Feng Chao-Wen
Publication year - 2009
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.58.4183
Subject(s) - computer science , cellular neural network , artificial neural network , discrete circuit , electronic circuit , capacitance , transistor , circuit design , equivalent circuit , integrated circuit , electronic engineering , artificial intelligence , electrical engineering , embedded system , physics , voltage , electrode , quantum mechanics , engineering , operating system
Based on both the cell equivalent circuit of cellular neural network and the electrical characteristic model of cellular neural networksCNN cellthe 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.