基于元胞非线性网络的气体传感识别

2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI:10.1109/CNNA49188.2021.9610754

M. M. Al Chawa, R. Picos, L. Panes-Ruiz, Leif Riemenschneider, B. Ibarlucea, G. Cuniberti, R. Tetzlaff

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引用次数: 2

摘要

在这项工作中，我们开发了一种信号处理细胞非线性网络(CNN)，用于从记忆性气体传感器矩阵中获得的真实传感器数据的检测和分类。使用气体传感器CNN，我们可以区分有害气体，如氨(NH3)和硫化氢(H2S)，并确定其浓度水平。

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Gas Sensing Discrimination using a Cellular Nonlinear Network

In this work, we developed a signal processing Cellular Nonlinear Network (CNN) for the detection and classification of real sensor data obtained from a memristive gas sensors matrix. Applying a gas sensor CNN we can discriminate between hazardous gases such as Ammonia (NH3) and Hydrogen Sulfide (H2S) and determine their concentration levels.

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来源期刊

2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)

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