Automatic digital modulation recognition based on stacked sparse autoencoder

In this paper, a modulation recognition algorithm based on Stacked sparse Auto-Encoder (SSAE) is proposed for the classification of common digitally modulated signals. To this end, a set of eight features including, two instantaneous features and six higher order cumulants features are extracted fro...

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Veröffentlicht in:	Proceedings (International Conference on Communication Technology. Online) S. 28 - 32
Hauptverfasser:	Bouchou, Mohamed, Wang, Hua, El Hadi Lakhdari, Mohammed
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.10.2017
Schlagworte:	Automatic Modulation Recognition (AMR) Classification algorithms Feature extraction Higher Order Cumulants (HOC) Phase shift keying Signal to noise ratio Stacked Sparse AutoEncoder (SSAE) Support vector machines Training
ISSN:	2576-7828
Online-Zugang:	Volltext
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