Gas Sensing Discrimination using a Cellular Nonlinear Network
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
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
| Originalsprache | Englisch |
|---|---|
| Titel | 2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers (IEEE) |
| ISBN (elektronisch) | 978-1-6654-3948-0 |
| ISBN (Print) | 978-1-6654-3949-7 |
| Publikationsstatus | Veröffentlicht - 2021 |
| Peer-Review-Status | Ja |
Publikationsreihe
| Reihe | IEEE International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) |
|---|---|
| ISSN | 2165-0160 |
Workshop
| Titel | 17th IEEE International Workshop on Cellular Nanoscale Networks and their Applications |
|---|---|
| Kurztitel | CNNA 2021 |
| Veranstaltungsnummer | 17 |
| Dauer | 29 September - 1 Oktober 2021 |
| Webseite | |
| Bekanntheitsgrad | Internationale Veranstaltung |
| Ort | University of Catania |
| Stadt | Catania |
| Land | Italien |
Externe 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 |
| ORCID | /0000-0002-6574-7848/work/211720466 |