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首页> 外文期刊>IETE Journal of Research >Application of Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System for the Modelling and Simulation of QCA Circuits
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Application of Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System for the Modelling and Simulation of QCA Circuits

机译:人工神经网络和自适应神经模糊推理系统在QCA电路建模与仿真中的应用

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摘要

In this paper, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used for the modelling and simulation of quantum-dot cellular automata (QCA) circuits. For this purpose, all QCA basis components and gates are modelled using ANN and ANFIS. The accuracy and performance of the proposed methods are analysed through a few circuits. Finally, we compared the simulation speed of the proposed methods with QCADesigner software. The results show that the proposed ANN and ANFIS models are much faster than QCADesigner. Also, these models are imported into HSPICE software to design and simulate complex QCA logic circuits.
机译:本文将人工神经网络(ANN)和自适应神经模糊推理系统(ANFIS)用于量子点细胞自动机(QCA)电路的建模和仿真。为此,使用ANN和ANFIS对所有QCA基础组件和门进行建模。通过几个电路分析了所提出方法的准确性和性能。最后,我们使用QCADesigner软件比较了所提出方法的仿真速度。结果表明,所提出的ANN和ANFIS模型比QCADesigner快得多。而且,这些模型被导入到HSPICE软件中,以设计和仿真复杂的QCA逻辑电路。

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