Classification of NDE Waveforms with Autoregressive Models

  • R. B. Melton
Part of the Library of Congress Cataloging in Publication Data book series (volume 2A)


This paper describes a new approach for classifying NDE waveforms. Using this approach a set of matched filters is constructed one for each category of waveform, based on parameters from autoregressive models. The method offers advantages in terms of hardware implementation over conventional pattern recognition approaches. Feasibility is shown using computer generated data. Results are then presented for real data from acoustic emission experiments.


Acoustic Emission Autoregressive Model Matched Filter Autoregressive Parameter Acoustic Emission Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Plenum Press, New York 1983

Authors and Affiliations

  • R. B. Melton
    • 1
  1. 1.Pacific Northwest LaboratoryRichlandUSA

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