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Description
  • The distribution mixture (DM) model is usually applied whenever there is a strong evidence of multimodality in the data which is the case of Acoustic Emission (AE) applications. Our scope is the following: to employ the divergence based set of signal classification attributes and to explore the possible use of the distribution mixture as a model based method in statistical AE classification and cluster analysis. The clusters are considered to be generated from the DM components with normal densities. We deal with the problem of optimal number of components of the mixture. The contaminated model with simulated misleading cluster is considered and comparative sensitivity study is produced to discover the basic stability and robustness properties of DM approach.
  • The distribution mixture (DM) model is usually applied whenever there is a strong evidence of multimodality in the data which is the case of Acoustic Emission (AE) applications. Our scope is the following: to employ the divergence based set of signal classification attributes and to explore the possible use of the distribution mixture as a model based method in statistical AE classification and cluster analysis. The clusters are considered to be generated from the DM components with normal densities. We deal with the problem of optimal number of components of the mixture. The contaminated model with simulated misleading cluster is considered and comparative sensitivity study is produced to discover the basic stability and robustness properties of DM approach. (en)
Title
  • Sensitivity of Acoustic Emission Classification under Distribution Mixtures
  • Sensitivity of Acoustic Emission Classification under Distribution Mixtures (en)
skos:prefLabel
  • Sensitivity of Acoustic Emission Classification under Distribution Mixtures
  • Sensitivity of Acoustic Emission Classification under Distribution Mixtures (en)
skos:notation
  • RIV/68407700:21340/11:00187897!RIV12-MSM-21340___
http://linked.open...avai/predkladatel
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  • S, Z(MSM6840770039)
http://linked.open...iv/cisloPeriodika
  • 7
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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  • 228838
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  • RIV/68407700:21340/11:00187897
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  • Classification attributes; phi-divergences; Signal separation; Robustness properties (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • SK - Slovenská republika
http://linked.open...ontrolniKodProRIV
  • [101E0E0530CF]
http://linked.open...i/riv/nazevZdroje
  • Forum Statisticum Slovacum
http://linked.open...in/vavai/riv/obor
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http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 8
http://linked.open...iv/tvurceVysledku
  • Kůs, Václav
  • Tláskal, Jan
http://linked.open...n/vavai/riv/zamer
issn
  • 1336-7420
number of pages
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  • 21340
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