Novel High-Efficiency Nanocomposite Gate Design of Quantum-Dot Cellular Automata Based on Deep Learning

Author:

Zhu Yourun1ORCID,Ren Senlin1,Li Xiaolong1

Affiliation:

1. College of Electronic Information, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China

Abstract

With the development of science and technology, the feature size of CMOS devices will always shrink to the limit. Therefore, some new nanodevices will eventually become substitutes for microelectronic devices. A new electronic revolution will break out. Nanoscience and technology is the high-tech frontier technology of the century and one of the main contents of scientific development in the new era. Its development will have a profound impact on other disciplines, industries, and society. Nanoelectronics is an important part of the discipline of nanoscience and technology, which represents the development trend of microelectronics and will become the foundation of the next generation of electronic science and technology. With the development of ultra-large-scale integrated circuits, the feature size of electronic devices is getting smaller and smaller and has entered the nanoscale from the microscale. When the size of the system is small enough to be compared with the wavelength of electrons, the quantum effect becomes the dominant current-carrying main factor in child behavior. While these new phenomena and new effects bring challenges to the original semiconductor devices, they also provide opportunities for the development of new devices. Evolutionary circuit design is based on cellular neural network and quantum-dot cells, designs combinational logic circuits through the evolutionary algorithm, uses the logic gate based on cellular neural network design as the population gene of evolutionary circuit design, enriches the diversity of the population, and improves the evolutionary algorithm at the same time, the success rate of the improved genetic algorithm for evolutionary circuits has been greatly improved, and the failure rate has been reduced from 14% to 2%, obtaining a faster evolution speed and improving the performance of the evolution circuit.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

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