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