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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F11%3APU95262%21RIV12-MSM-26220___
rdf:type
n10:Vysledek skos:Concept
dcterms:description
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. 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.
dcterms:title
Feature-Based Classification of Digital Modulations Using Various Learning Algorithms Feature-Based Classification of Digital Modulations Using Various Learning Algorithms
skos:prefLabel
Feature-Based Classification of Digital Modulations Using Various Learning Algorithms Feature-Based Classification of Digital Modulations Using Various Learning Algorithms
skos:notation
RIV/00216305:26220/11:PU95262!RIV12-MSM-26220___
n10:predkladatel
n16:orjk%3A26220
n3:aktivita
n6:S n6:P n6:Z
n3:aktivity
P(GP102/09/P626), S, Z(MSM0021630513)
n3:dodaniDat
n8:2012
n3:domaciTvurceVysledku
Kubánková, Anna n18:2629291 n18:2066386
n3:druhVysledku
n13:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n23:predkladatel
n3:idSjednocenehoVysledku
199467
n3:idVysledku
RIV/00216305:26220/11:PU95262
n3:jazykVysledku
n14:eng
n3:klicovaSlova
classification of digital modulations, features, machine learning algorithm
n3:klicoveSlovo
n5:machine%20learning%20algorithm n5:features n5:classification%20of%20digital%20modulations
n3:kontrolniKodProRIV
[F1AF460F48BD]
n3:mistoKonaniAkce
Těchov
n3:mistoVydani
Brno, Czech Republic
n3:nazevZdroje
The 13th International Conference on Research in Telecommunication Technologies RTT - 2011
n3:obor
n15:JA
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
4
n3:projekt
n12:GP102%2F09%2FP626
n3:rokUplatneniVysledku
n8:2011
n3:tvurceVysledku
Burget, Radim Kubánková, Anna Ganiyev, Artem Kubánek, David
n3:typAkce
n4:WRD
n3:zahajeniAkce
2011-09-07+02:00
n3:zamer
n9:MSM0021630513
s:numberOfPages
4
n21:hasPublisher
Vysoké učení technické v Brně
n19:isbn
978-80-214-4283-2
n17:organizacniJednotka
26220