| dc.contributor.author | Özmen, Atilla | |
| dc.contributor.author | Tander, Baran | |
| dc.date.accessioned | 2019-06-27T08:05:28Z | |
| dc.date.available | 2019-06-27T08:05:28Z | |
| dc.date.issued | 2010 | |
| dc.identifier.isbn | 978-1-4244-5795-3 | |
| dc.identifier.issn | 2158-8481 | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12469/1078 | |
| dc.identifier.uri | https://doi.org/10.1109/MELCON.2010.5476301 | |
| dc.description.abstract | In this paper a dynamic neural network structure called Cellular Neural Network (CNN) is employed for the equalization in digital communication. It is shown that this nonlinear system is capable of suppressing the effect of intersymbol interference (ISI) and the noise at the channel. The architecture is a small-scaled simple CNN containing 9 neurons thus having only 19 weight coefficients. Proposed system is compared with linear transversal filters as well as with a Multilayer Perceptron (MLP) based equalizer. | en_US] |
| dc.language.iso | eng | en_US |
| dc.publisher | IEEE | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | N/A | en_US |
| dc.title | Channel Equalization with Cellular Neural Networks | en_US |
| dc.type | conferenceObject | en_US |
| dc.identifier.startpage | 1597 | en_US |
| dc.identifier.endpage | 1599 | |
| dc.relation.journal | Melecon 2010: The 15th IEEE Mediterranean Electrotechnical Conference | en_US |
| dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
| dc.identifier.wos | WOS:000286988200291 | en_US |
| dc.identifier.doi | 10.1109/MELCON.2010.5476301 | en_US |
| dc.identifier.scopus | 2-s2.0-77954301461 | en_US |
| dc.institutionauthor | Özmen, Atilla | en_US |
| dc.institutionauthor | Tander, Baran | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
