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dc.contributor.authorMassey, David E.*
dc.date.accessioned2016-06-06T22:02:31Z
dc.date.available2016-06-06T22:02:31Z
dc.date.issued1992-10
dc.identifier.issn0884-5123
dc.identifier.issn0074-9079
dc.identifier.urihttp://hdl.handle.net/10150/611917
dc.descriptionInternational Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, Californiaen_US
dc.description.abstractThis 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.sponsorshipInternational Foundation for Telemeteringen
dc.language.isoen_USen
dc.publisherInternational Foundation for Telemeteringen
dc.relation.urlhttp://www.telemetry.org/en
dc.rightsCopyright © International Foundation for Telemeteringen
dc.titleNeural Network Application to Telemetry Frame Synchronizationen_US
dc.typetexten
dc.typeProceedingsen
dc.contributor.departmentGoddard Space Flight Centeren
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.description.collectioninformationProceedings 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.dateFOA2018-09-11T11:55:39Z
html.description.abstractThis 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.


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