A modulation classification method in cognitive radios system using stacked denoising sparse autoencoder

This paper proposes a modulation classification method based on Stacked Denoising Sparse Autoencoder (SDAE). This method can extract modulation features automatically, and classify input signals based on the features it extracts. The scenarios of rapid classification and high accuracy classification...

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Bibliographic Details

Published in:	Proceedings (IEEE Radio and Wireless Symposium. Online) pp. 218 - 220
Main Authors:	Xu Zhu, Fujii, Takeo
Format:	Conference Proceeding
Language:	English Japanese
Published:	IEEE 01.01.2017
Subjects:	Cognitive radio Feature extraction machine learning Manganese Modulation modulation classification Noise reduction Resistance Training
ISSN:	2164-2974
Online Access:	Get full text
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