Detail publikace

Feature-Based Classification of Digital Modulations Using Various Learning Algorithms

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

4

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"
}