About: Gaussian Mixture Models-based Recognition of Digital Modulations of Noisy Signals

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://www.elektrorevue.cz
Description	A novel approach to the recognition of digital modulations is presented. It is based on features that characterize a specific kind of modulation or a group of modulations. These features are calculated from the instantaneous amplitude, instantaneous phase, and spectrum symmetry of the unknown signal. To recognize the modulations, an analysis of the features is carried out by means of a classifier based on Gaussian mixture models. The method was designed for 2ASK, 2FSK, MSK, BPSK, QPSK, and 16QAM modulations. They belong to the widely used digital modulations in recent communication systems. Simulation results demonstrating performance of the method are presented. The testing signals are corrupted by white Gaussian noise. A novel approach to the recognition of digital modulations is presented. It is based on features that characterize a specific kind of modulation or a group of modulations. These features are calculated from the instantaneous amplitude, instantaneous phase, and spectrum symmetry of the unknown signal. To recognize the modulations, an analysis of the features is carried out by means of a classifier based on Gaussian mixture models. The method was designed for 2ASK, 2FSK, MSK, BPSK, QPSK, and 16QAM modulations. They belong to the widely used digital modulations in recent communication systems. Simulation results demonstrating performance of the method are presented. The testing signals are corrupted by white Gaussian noise. (en)
Title	Gaussian Mixture Models-based Recognition of Digital Modulations of Noisy Signals Gaussian Mixture Models-based Recognition of Digital Modulations of Noisy Signals (en)
skos:prefLabel	Gaussian Mixture Models-based Recognition of Digital Modulations of Noisy Signals Gaussian Mixture Models-based Recognition of Digital Modulations of Noisy Signals (en)
skos:notation	RIV/00216305:26220/11:PU94354!RIV12-MSM-26220___
http://linked.open...avai/predkladatel	Fakulta elektrotechniky a komunikačních technologií
http://linked.open...avai/riv/aktivita	P S Z
http://linked.open...avai/riv/aktivity	P(GP102/09/P626), S, Z(MSM0021630513)
http://linked.open...iv/cisloPeriodika	1
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Atassi, Hicham Kubánek, David Kubánková, Anna
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoké učení technické v Brně / Fakulta elektrotechniky a komunikačních technologií
http://linked.open...dnocenehoVysledku	200837
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/11:PU94354
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Recognition of Digital Modulations, Classification of Digital Modulations, Gaussian Mixture Models (en)
http://linked.open.../riv/klicoveSlovo	Classification of Digital Modulations Gaussian Mixture Models Recognition of Digital Modulations
http://linked.open...odStatuVydavatele	CZ - Česká republika
http://linked.open...ontrolniKodProRIV	[F0EF536437D7]
http://linked.open...i/riv/nazevZdroje	Elektrorevue - Internetový časopis (http://www.elektrorevue.cz)
http://linked.open...in/vavai/riv/obor	JA
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Automatic Classification of Digital Modulations
http://linked.open...UplatneniVysledku	2011
http://linked.open...v/svazekPeriodika	2
http://linked.open...iv/tvurceVysledku	Atassi, Hicham Kubánek, David Kubánková, Anna
http://linked.open...n/vavai/riv/zamer	Advanced Electronic Communication Systems and Technologies (ELCOM)
issn	1213-1539
number of pages	8 (xsd:int)
http://localhost/t...ganizacniJednotka	26220
is http://linked.open...avai/riv/vysledek of	Gaussian Mixture Models-based Recognition of Digital Modulations of Noisy Signals Gaussian Mixture Models-based Recognition of Digital Modulations of Noisy Signals

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