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KUBÁNKOVÁ, A. BURGET, R. KUBÁNEK, D. GANIYEV, A.
Originální název
Feature-Based Classification of Digital Modulations Using Various Learning Algorithms
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
The paper deals with classification of digital modulations by means of ten characteristic features of modulated signal and four learning algorithms, namely Artificial Neural Networks, Support Vector Machines, k-Nearest neighbors, and Random Forests. 2ASK, 2FSK, 4FSK, MSK, BPSK, QPSK, 8PSK, and 16QAM modulations were chosen for classification. Testing of the methods was carried out by simulation with signals disturbed by multipath fading and additive white Gaussian noise. It was found out that the Random Forests algorithm provides best results with over 99 % accuracy.
Klíčová slova
classification of digital modulations; features; machine learning algorithm
Autoři
KUBÁNKOVÁ, A.; BURGET, R.; KUBÁNEK, D.; GANIYEV, A.
Rok RIV
2011
Vydáno
7. 9. 2011
Nakladatel
Brno University of Technology
Místo
Brno, Czech Republic
ISBN
978-80-214-4283-2
Kniha
The 13th International Conference on Research in Telecommunication Technologies RTT - 2011
Strany od
1
Strany do
4
Strany počet
BibTex
@inproceedings{BUT75345, author="Anna {Kubánková} and Radim {Burget} and David {Kubánek} and Artem {Ganiyev}", title="Feature-Based Classification of Digital Modulations Using Various Learning Algorithms", booktitle="The 13th International Conference on Research in Telecommunication Technologies RTT - 2011", year="2011", pages="1--4", publisher="Brno University of Technology", address="Brno, Czech Republic", isbn="978-80-214-4283-2" }