Title :
Modeling of Neuron Based on Single Electron Transistor
Author :
Qiu, Peng ; Wang, Guanglong ; Lu, Jianglei ; Feng, Shuang
Author_Institution :
Coll. of Mech. Eng., Inst. of Nanotechnol. & Microsyst., Shijiazhuang, China
Abstract :
As the basic unit of cell neural network (CNN), neuron has been the focus of the research of CNN. This paper introduces a modeling method of neuron that is based on single electron transistor (SET). SET is a kind of nano electronic device, which has come to be considered candidate as the basic element for future low power, high density integrated circuits, and the quantum effect of SET shows two basic characteristics: Coulomb oscillation and Coulomb blockade. According to the nonlinear equation of neuron, a neuron can be divided into three modules: cell module, feedback template module and control template module. An equivalent structure of neuron based on these three modules is put forward. The modeling circuits that match the requirement of neuron equations are designed with SETs in the end of this paper.
Keywords :
Coulomb blockade; cellular neural nets; nanoelectronics; nonlinear equations; single electron transistors; Coulomb blockade; Coulomb oscillation; cell module; cell neural network; control template module; feedback template module; high density integrated circuits; nanoelectronic device; neuron modeling; nonlinear neuron equation; quantum effect; single electron transistor; Cellular neural networks; Computer networks; Electrodes; Integrated circuit interconnections; Neural networks; Neurons; Nonlinear equations; Single electron transistors; Tunneling; Voltage;
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
DOI :
10.1109/CSO.2009.181