Correlation between Sensing Accuracy and Read Margin of a Memristor-Based NO Gas Sensor Array Estimated by Neural Network Analysis-Reference-Cited by-同舟云学术

Correlation between Sensing Accuracy and Read Margin of a Memristor-Based NO Gas Sensor Array Estimated by Neural Network Analysis

Published:2023-05-10 Issue:5 Volume:8 Page:2105-2114
ISSN:2379-3694
Container-title:ACS Sensors
language:en
Short-container-title:ACS Sens.

Author:

Lee Doowon¹^ORCID,Chae Myoungsu¹,Jung Jinsu¹,Kim Hee-Dong¹^ORCID

Affiliation:

1. Department of Electrical Engineering, Semiconductor Systems Engineering, and Convergence Engineering for Intelligent Drone, Institute of Semiconductor and System IC, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea

Funder

National Research Foundation of Korea

Korea Institute for Advancement of Technology

Publisher

American Chemical Society (ACS)

Subject

Fluid Flow and Transfer Processes,Process Chemistry and Technology,Instrumentation,Bioengineering

Link

https://pubs.acs.org/doi/pdf/10.1021/acssensors.3c00541

Reference22 articles.

1. Machine learning-based discrimination of indoor pollutants using an oxide gas sensor array: High endurance against ambient humidity and temperature

2. Monitoring reliability of sensors in an array by neural networks

3. Field calibration of a cluster of low-cost commercially available sensors for air quality monitoring. Part B: NO, CO and CO2

4. Diagnostic Performance of an Electronic Nose, Fractional Exhaled Nitric Oxide, and Lung Function Testing in Asthma

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