Feature Analysis of Time and Frequency Domain for Automatic Modulation Classification

dc.contributor.author	Güner, Ahmet
dc.contributor.author	Alçin, Ömer Faruk
dc.contributor.author	Üstündağ, Mehmet
dc.date.accessioned	2016-09-19T12:52:53Z
dc.date.available	2016-09-19T12:52:53Z
dc.date.issued	2016-09-17
dc.identifier.uri	http://acikerisim.bingol.edu.tr/handle/20.500.12898/1045
dc.description.abstract	In this study, determination of the type of digital modulation of received signal in communication systems was aimed. For this purpose, high order cumulants, which are the most addressed ones, and frequency-based features were together examined for improving performance of classifier. Simulation studies were performed to evaluate the effect of these features on performance of classifier, both separately and together. Performed simulation studies showed that the proposed approach had higher performance	tr_TR
dc.publisher	International Artificial Intelligence and Data Processing Symposium'16	tr_TR
dc.subject	High order cumulants	tr_TR
dc.subject	median frequency	tr_TR
dc.subject	mean frequency	tr_TR
dc.subject	mean Lomb-Scargle Periodogram	tr_TR
dc.subject	extreme learning machine	tr_TR
dc.title	Feature Analysis of Time and Frequency Domain for Automatic Modulation Classification	tr_TR
dc.type	Presentation	tr_TR