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Source depth discrimination with a vertical line array.
Conan, Ewen; Bonnel, Julien; Chonavel, Thierry; Nicolas, Barbara.
Afiliação
  • Conan E; Laboratoire des Sciences et Techniques de l'Information, de la Communication et de la Connaissance, Unité Mixte de Recherche, Centre National de la Recherche Scientifique 6285, École Nationale Supérieure de Techniques Avancées, Bretagne, 2 rue François Verny, 29806 Brest Cedex 9, France ewen.conan@e
  • Bonnel J; Laboratoire des Sciences et Techniques de l'Information, de la Communication et de la Connaissance, Unité Mixte de Recherche, Centre National de la Recherche Scientifique 6285, École Nationale Supérieure de Techniques Avancées, Bretagne, 2 rue François Verny, 29806 Brest Cedex 9, France ewen.conan@e
  • Chonavel T; Laboratoire des Sciences et Techniques de l'Information, de la Communication et de la Connaissance, Unité Mixte de Recherche, Centre National de la Recherche Scientifique 6285, Télécom Bretagne, 655 Avenue du Technopole, 29200 Plouzané, France thierry.chonavel@telecom-bretagne.eu.
  • Nicolas B; Université de Lyon, Centre de Recherche en Applications et Traitement de l'image pour la Santé, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 5220, Inserm U1044, Institut National des Sciences Appliquées Lyon, Université Claude Bernard Lyon 1, Francebarbara.nicolas@creatis.i
J Acoust Soc Am ; 140(5): EL434, 2016 11.
Article em En | MEDLINE | ID: mdl-27908045
Source depth estimation with a vertical line array generally involves mode filtering, then matched-mode processing. Because mode filtering is an ill-posed problem if the water column is not well-sampled, concerns for robustness motivate a simpler approach: source depth discrimination considered as a binary classification problem. It aims to evaluate whether the source is near the surface or submerged. These two hypotheses are formulated in terms of normal modes, using the concept of trapped and free modes. Decision metrics based on classic mode filters are proposed. Monte Carlo methods are used to predict performance and set the parameters of a classifier accordingly.
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Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article
Buscar no Google
Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article