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Your search keyword '"Quan-Xin Deng"' showing total 3 results
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3 results on '"Quan-Xin Deng"'

1. Memristor-based genetic algorithm for image restoration

Author

Yong-Bin Yu, Chen Zhou, Quan-Xin Deng, Yuan-Jing-Yang Zhong, Man Cheng, and Zheng-Fei Kang

Subjects
Biological intelligence, Genetic algorithm (GA), Image restoration, Memristor, Electronic computers. Computer science, QA75.5-76.95, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

This paper explores a way of deploying the classical algorithm named genetic algorithm (GA) with the memristor. The memristor is a type of circuit device with both characteristics of storage and computing, which provides the similarity between electronic devices and biological components, such as neurons, and the structure of the memristor-based array is similar to that of chromosomes in genetics. Besides, it provides the similarity to the image gray-value matrix that can be applied to image restoration with GA. Thus, memristor-based GA is proposed and the experiment about image restoration using memristor-based GA is carried out in this paper. And parameters, such as the size of initial population and the number of iterations, are also set different values in the experiment, which demonstrates the feasibility of implementing GA with memristors.1

Published
2022
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3. [Comparative Analysis of the Bacterial Community on Anodic Biofilms in Sediment Microbial Fuel Cell Under Open and Closed Circuits]

Author

Yi-Cheng, Wu, Quan-Xin, Deng, Ze-Jie, Wang, Yue, Zheng, Dai-Lin, Li, and Feng, Zhao

Subjects
Electron Transport, Bacteria, Bioelectric Energy Sources, Biofilms, Electrodes
Abstract

To investigate the differences in microbial community of anodic biofilms under open and closed circuits, sediment microbial fuel cell (SMFCs) reactors connecting with a 5 kΩ external resistance and open circuit during the start-up period were operated individually. Anodic biofilms were collected and analyzed using Solexa high-throughput sequencing technology. A total of 3936 and 3930 operational taxonomic units (OTUs) were obtained from the anodic biofilms under open and closed circuits, respectively. After 97% similarity merging, 1581 and 1551 OTUs were finally determined from open and close circuit biofilms, respectively. The analysis of α diversity showed that bacterial diversity of anodic biofilm under open circuit was higher than that under closed circuit. The dominant bacterial were Proteobacteria, Firmicutes and Bacteroidetes for both open and closed circuits. They accounted for 59.79%, 12.54% and 9.02% under open circuit biofilm respectively; and these values were 63.02%, 10.01% and 3.60% in the closed circuit biofilm respectively, and

Published
2018

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