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  • This work deals with pertinent application of signal source location method by means of neural network. As a source an acoustic emission signal was used. Among the most important parameters participating in the final results was the correct measurement method and signal processing choice. For the source signal location the back propagation-type neural network was used. Thanks to this network‘s ability to ‚learn‘ and adapt to ambient conditions, represented by jamming signals, it was possible to takke these into account. The problem dealt with was the choice of suitable signal parameters of all the parameters obtained by measurement. These parameters then represented the neural network inputs and influenced its results. Therefore, it was necessary to make several experimental measurements. As the final ones were selected those, with which the neural network results gave the most accurate values. The accuracy evaluation was done by comparing the neural network outputs with required values of coor
  • This work deals with pertinent application of signal source location method by means of neural network. As a source an acoustic emission signal was used. Among the most important parameters participating in the final results was the correct measurement method and signal processing choice. For the source signal location the back propagation-type neural network was used. Thanks to this network‘s ability to ‚learn‘ and adapt to ambient conditions, represented by jamming signals, it was possible to takke these into account. The problem dealt with was the choice of suitable signal parameters of all the parameters obtained by measurement. These parameters then represented the neural network inputs and influenced its results. Therefore, it was necessary to make several experimental measurements. As the final ones were selected those, with which the neural network results gave the most accurate values. The accuracy evaluation was done by comparing the neural network outputs with required values of coor (en)
Title
  • Signal Source Location by Means of Neural Network
  • Signal Source Location by Means of Neural Network (en)
skos:prefLabel
  • Signal Source Location by Means of Neural Network
  • Signal Source Location by Means of Neural Network (en)
skos:notation
  • RIV/00216305:26220/02:PU30568!RIV/2003/MSM/262203/N
http://linked.open.../vavai/riv/strany
  • 99-105
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM 260000013), Z(MSM 262200022)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 663486
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/02:PU30568
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • acoustic emission, neural network, location (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [21D5DBBF1AD8]
http://linked.open...v/mistoKonaniAkce
  • Praha
http://linked.open...i/riv/mistoVydani
  • Praha
http://linked.open...i/riv/nazevZdroje
  • 25th European Conference on Acoustic Emission Testing
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...ocetUcastnikuAkce
http://linked.open...nichUcastnikuAkce
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Jirsík, Václav
  • Černý, Luděk
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • EWGAE
https://schema.org/isbn
  • 80-214-2174-6
http://localhost/t...ganizacniJednotka
  • 26220
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