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  • We deal with the classification of acoustic emission signals by means of Fuzzy Clustering (FC), Model-Based Clustering (MBC) and Support Vector Machines (SVM). These methods belong to a different group of classification techniques, e.g. the SVM is searching for optimal separating hyperplanes between clusters. The signals are compared by means of suitable parameters obtained directly from the signals and from normed frequency spectra such as phi-divergence distance measure as the additional attribute. We are concerned with resulting cluster comparisons and the selection of efficient classification parameters. We realize three experiments in the area of acoustic emission to test the proposed classification methods by means of laboratory data and also considering industrial data from the real life.
  • We deal with the classification of acoustic emission signals by means of Fuzzy Clustering (FC), Model-Based Clustering (MBC) and Support Vector Machines (SVM). These methods belong to a different group of classification techniques, e.g. the SVM is searching for optimal separating hyperplanes between clusters. The signals are compared by means of suitable parameters obtained directly from the signals and from normed frequency spectra such as phi-divergence distance measure as the additional attribute. We are concerned with resulting cluster comparisons and the selection of efficient classification parameters. We realize three experiments in the area of acoustic emission to test the proposed classification methods by means of laboratory data and also considering industrial data from the real life. (en)
Title
  • STATISTICAL METHODS IN SIGNAL PROCESSING AND DISCRIMINATION
  • STATISTICAL METHODS IN SIGNAL PROCESSING AND DISCRIMINATION (en)
skos:prefLabel
  • STATISTICAL METHODS IN SIGNAL PROCESSING AND DISCRIMINATION
  • STATISTICAL METHODS IN SIGNAL PROCESSING AND DISCRIMINATION (en)
skos:notation
  • RIV/68407700:21340/10:00176076!RIV11-MSM-21340___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S, Z(MSM6840770039)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
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  • 289943
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21340/10:00176076
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Signal classification; phi-divergences; Fuzzy method; Model-Based method; SVM method; Real data processing (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D02EEC34FC56]
http://linked.open...v/mistoKonaniAkce
  • Plzeň
http://linked.open...i/riv/mistoVydani
  • Brno
http://linked.open...i/riv/nazevZdroje
  • DEFEKTOSKOPIE 2010 NDE for Safety PROCEEDINGS 40th International Conference
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
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http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kůs, Václav
  • Farová, Zuzana
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Vysoké učení technické v Brně
https://schema.org/isbn
  • 978-80-214-4182-8
http://localhost/t...ganizacniJednotka
  • 21340
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