Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning

HIGHLIGHTS

• who: Léonard Seydoux from the CNRS Rice University have published the research: Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning, in the Journal: NATURE COMMUNICATIONS NATURE COMMUNICATIONS of June/17,/2017
• what: The authors develop a new unsupervised deep-learning method for clustering signals in continuous multichannel seismic time series. To follow the idea of optimal wavelet design in a fully explorative way, the authors propose to learn the mother wavelet of each filterbank with respect to the clustering loss. The authors develop and apply the strategy to . . .
  

   

  

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