A novel modulation classification method in cognitive radios using higher-order cumulants and denoising stacked sparse autoencoder

In this paper, we propose a novel modulation classification method based on deep network as well as higher-order cumulants. The proposed algorithm uses the higher-order cumulants as the features, and thus achieves impressive noise suppression. We use Stacked Denoising Sparse Autoencoder as a classif...

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Veröffentlicht in:	2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA) S. 1 - 5
Hauptverfasser:	Xu Zhu, Fujii, Takeo
Format:	Tagungsbericht
Sprache:	Englisch Japanisch
Veröffentlicht:	Asia Pacific Signal and Information Processing Association 01.12.2016
Schlagworte:	Cognitive radio Cost function Feature extraction Manganese Modulation Noise reduction Training
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