Neural Network Application to Telemetry Frame Synchronization
| dc.contributor.author | Massey, David E. | |
| dc.date.accessioned | 2016-06-06T22:02:31Z | |
| dc.date.available | 2016-06-06T22:02:31Z | |
| dc.date.issued | 1992-10 | |
| dc.identifier.issn | 0884-5123 | |
| dc.identifier.issn | 0074-9079 | |
| dc.identifier.uri | http://hdl.handle.net/10150/611917 | |
| dc.description | International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California | en_US |
| dc.description.abstract | This paper looks into the use of neural network software as applied to the classical signal to noise concern when dealing with space to ground data communications. Use of a digital neural network to extend the correlation range of Pulse Code Modulation (PCM) down into noise is investigated. Conventional synchronization pattern correlation is done with digital logic comparisons on a sliding window with a set number of bit mismatch errors allowed. Correlation with a neural network does pattern recognition with a weighted network of artificial neurons that have been trained to recognize the sync pattern within noise. The output of such a neural network will produce a best guess of the correct pattern. | |
| dc.description.sponsorship | International Foundation for Telemetering | en |
| dc.language.iso | en_US | en |
| dc.publisher | International Foundation for Telemetering | en |
| dc.relation.url | http://www.telemetry.org/ | en |
| dc.rights | Copyright © International Foundation for Telemetering | en |
| dc.title | Neural Network Application to Telemetry Frame Synchronization | en_US |
| dc.type | text | en |
| dc.type | Proceedings | en |
| dc.contributor.department | Goddard Space Flight Center | en |
| dc.identifier.journal | International Telemetering Conference Proceedings | en |
| dc.description.collectioninformation | Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection. | en |
| refterms.dateFOA | 2018-09-11T11:55:39Z | |
| html.description.abstract | This paper looks into the use of neural network software as applied to the classical signal to noise concern when dealing with space to ground data communications. Use of a digital neural network to extend the correlation range of Pulse Code Modulation (PCM) down into noise is investigated. Conventional synchronization pattern correlation is done with digital logic comparisons on a sliding window with a set number of bit mismatch errors allowed. Correlation with a neural network does pattern recognition with a weighted network of artificial neurons that have been trained to recognize the sync pattern within noise. The output of such a neural network will produce a best guess of the correct pattern. |
