Gas Sensing Discrimination using a Cellular Nonlinear Network
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
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.
Details
| Original language | English |
|---|---|
| Title of host publication | 2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (electronic) | 978-1-6654-3948-0 |
| ISBN (print) | 978-1-6654-3949-7 |
| Publication status | Published - 2021 |
| Peer-reviewed | Yes |
Publication series
| Series | IEEE International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) |
|---|---|
| ISSN | 2165-0160 |
Conference
| Title | 2021 17th IEEE International Workshop on Cellular Nanoscale Networks and their Applications |
|---|---|
| Abbreviated title | CNNA 2021 |
| Conference number | 17 |
| Duration | 29 September - 1 October 2021 |
| Location | University of Catania |
| City | Catania |
| Country | Italy |
External IDs
| ORCID | /0000-0001-7436-0103/work/142240392 |
|---|---|
| ORCID | /0000-0002-3007-8840/work/142247151 |
| ORCID | /0000-0002-9899-1409/work/142249234 |
| ORCID | /0000-0001-8886-4708/work/172572514 |