Modeling and classification of biological signals
dc.contributor.advisor | Cristi, Roberto | |
dc.contributor.advisor | Fargues, Monique P. | |
dc.contributor.author | VanDerKamp, Martha M. | |
dc.date.accessioned | 2012-11-29T16:18:47Z | |
dc.date.available | 2012-11-29T16:18:47Z | |
dc.date.issued | 1992-12 | |
dc.identifier.uri | https://hdl.handle.net/10945/23965 | |
dc.description.abstract | This thesis examines a number of marine biological signals and the problem of modeling by autoregressive techniques using a prony-svd algorithm to accurately represent segments of biological signals. Two methods are employed to classify the biological signals from the model parameters. The first classification method is based on a Neural Network implementation using a commercial software package. The second method is accomplished by using a distance measure, based on spectral ratios, with respect to modeled reference signals. | en_US |
dc.description.uri | http://archive.org/details/modelingndclassi1094523965 | |
dc.format.extent | 88 p.;28 cm. | en_US |
dc.language.iso | en_US | |
dc.publisher | Monterey, California. Naval Postgraduate School | en_US |
dc.title | Modeling and classification of biological signals | en_US |
dc.type | Thesis | en_US |
dc.contributor.corporate | Naval Postgraduate School | |
dc.contributor.school | Naval Postgraduate School | |
dc.contributor.department | Electrical and Computer Engineering | |
dc.description.service | Lieutenant, United States Navy | en_US |
etd.thesisdegree.name | M.S. in Electrical Engineering | en_US |
etd.thesisdegree.level | Masters | en_US |
etd.thesisdegree.discipline | Electrical Engineering | en_US |
etd.thesisdegree.grantor | Naval Postgraduate School | en_US |
dc.description.distributionstatement | Approved for public release; distribution is unlimited. |
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