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

Smyth, Padhraic

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