摘要
基于细胞神经网络(CNN)细胞单元的等效电路及其电学特性模型,利用SET-MOS混合结构反相器实现了模型中的激活函数电路,用耦合电容单元实现CNN细胞的系统模板,构建了SET-MOSCNN细胞硬件电路,并将其应用在图像处理中.仿真结果表明,所设计的CNN硬件电路具有结构简单、功耗低、响应速度快等特点,可用于构成各种规模的CNN电路,进一步满足大规模信号处理的需求及提高集成电路的集成度.
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.
出处
《物理学报》
SCIE
EI
CAS
CSCD
北大核心
2009年第6期4183-4188,共6页
Acta Physica Sinica
基金
陕西省自然科学基金(批准号:2005F20)
空军工程大学科研基金(批准号:2005ZK19)资助的课题~~
关键词
单电子晶体管
MOS管
细胞神经网络
图像处理
single electron transistor, MOS transistor, cellular neural networks, image processing
