Biologically Inspired Radio Signal Feature Extraction with Sparse Denoising Autoencoders

Automatic modulation classification (AMC) is an important task for modern communication systems; however, it is a challenging problem when signal features and precise models for generating each modulation may be unknown. We present a new biologically-inspired AMC method without the need for models o...

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Hauptverfasser:	Migliori, Benjamin, Zeller-Townson, Riley, Grady, Daniel, Gebhardt, Daniel
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Computer Science - Neural and Evolutionary Computing Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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