Show simple item record

dc.contributor.advisorTherrien, Charles W.
dc.contributor.authorHawes, Anthony H.
dc.dateSeptember 2003
dc.date.accessioned2012-03-14T17:48:29Z
dc.date.available2012-03-14T17:48:29Z
dc.date.issued2003-09
dc.identifier.urihttp://hdl.handle.net/10945/6312
dc.descriptionApproved for public release; distribution in unlimited.en_US
dc.description.abstractThis thesis addresses the problem of estimating a random process from two observed signals sampled at different rates. The case where the low-rate observation has a higher signal-to- noise ratio than the high-rate observation is addressed. Both adaptive and non-adaptive filtering techniques are explored. For the non-adaptive case, a multirate version of the Wiener-Hopf optimal filter is used for estimation. Three forms of the filter are described. It is shown that using both observations with this filter achieves a lower mean-squared error than using either sequence alone. Furthermore, the amount of training data to solve for the filter weights is comparable to that needed when using either sequence alone. For the adaptive case, a multirate version of the LMS adaptive algorithm is developed. Both narrowband and broadband interference are removed using the algorithm in an adaptive noise cancellation scheme. The ability to remove interference at the high rate using observations taken at the low rate without the high-rate observations is demonstrated.en_US
dc.description.urihttp://archive.org/details/leastsquaresndda109456312
dc.format.extentxvi, 47 p. : ill. (some col) ;en_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.subject.lcshEstimation theoryen_US
dc.subject.lcshLeast squaresen_US
dc.titleLeast squares and adaptive multirate filteringen_US
dc.typeThesisen_US
dc.contributor.secondreaderCristi, Roberto
dc.contributor.departmentElectrical and Computer Engineering
dc.subject.authorMultirate filteringen_US
dc.subject.authorAdaptive filteringen_US
dc.subject.authorMultirate Adaptive Filteren_US
dc.subject.authorMultirate Optimal Filteren_US
dc.subject.authorLeast squares Filteringen_US
dc.description.serviceLieutenant, United States Coast Guarden_US
etd.thesisdegree.nameM.S. in Electrical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record