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Hideen Markov Models and Neural Networks for Fault Detection in Dynamic Systems

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dc.contributor.author Smyth, Padhraic en_US
dc.date.accessioned 2004-10-05T23:48:07Z
dc.date.available 2004-10-05T23:48:07Z
dc.date.issued 1994-05-11 en_US
dc.identifier.citation Jet Propulsion Laboratory (JPL), Pasadena, California, USA en_US
dc.identifier.clearanceno 94-0713 en_US
dc.identifier.uri http://hdl.handle.net/2014/34368
dc.description.abstract None given. (From conclusion): Neural networks plus Hidden Markov Models(HMM)can provide excellene detection and false alarm rate performance in fault detection applications. Modified models allow for novelty detection. Also covers some key contributions of neural network model, and application status. en_US
dc.format.extent 310042 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject.other neural networks hidden markov model fault detection dynamic systems DSN deep space network en_US
dc.title Hideen Markov Models and Neural Networks for Fault Detection in Dynamic Systems en_US


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