单电子电路的鲁棒性研究

Researching the robustness of single electron devices

分析了单电子器件和人工神经网络的特性,从理论上证明了用人工神经网络构建单电子电路的可行性,并对单电子器件隧穿结隧穿特性和单电子振荡器的功能进行了仿真分析验证,同时研究了单电子振荡器的应用.本着可靠和复杂度低的前提,应用人工神经网络构建了一个单电子电路加法器模型,从模型的鲁棒性角度和电路的复杂性角度,用仿真软件对其进行了仿真分析.结果表明,神经网络是构建鲁棒性单电子电路的可靠方法,Pspice能够为成为单电子电路仿真的有效工具,为以后相关研究奠定了一定基础.

This article analyses the features of single electron devices in an artificial neural network. The feasibility of constructing single electron circuits using an artificial neural network is proved theoretically. Then, its tunneling effect and the function of a single electron oscillator were simulated and verified. Based on this, the applicability of a single electron oscillator was researched, and a single electron adder was created using an artificial neural net- work. Simulations were made to check its reliability and reduce the complexity of the circuit as much as possible. The results show that a neural network is an efficient method for the construction of a robust single electron circuit, and Pspice is an effective tool for the simulation of an SET circuit.