About: Gaussian Mixture Models-based Recognition of Digital Modulations of Noisy Signals     Goto   Sponge   NotDistinct   Permalink

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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/riv/aktivita
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
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  • 200837
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/11:PU94354
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Recognition of Digital Modulations, Classification of Digital Modulations, Gaussian Mixture Models (en)
http://linked.open.../riv/klicoveSlovo
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)
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http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 2
http://linked.open...iv/tvurceVysledku
  • Atassi, Hicham
  • Kubánek, David
  • Kubánková, Anna
http://linked.open...n/vavai/riv/zamer
issn
  • 1213-1539
number of pages
http://localhost/t...ganizacniJednotka
  • 26220
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