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dc.contributor.advisorTummala, Murali
dc.contributor.authorKim, Yong Joo
dc.dateDecember 1989
dc.date.accessioned2013-01-23T21:53:33Z
dc.date.available2013-01-23T21:53:33Z
dc.date.issued1989
dc.identifier.urihttp://hdl.handle.net/10945/25715
dc.description.abstractWe use a block Lanczos algorithm for computing a few of the smallest eigenvalues and the corresponding eigenvectors of a large symmetric matrix rather than computing all the eigenvalue-eigenvector pairs. The basic Lanczos algorithm generates a similar matrix which is block tridiagonal from a given large symmetric matrix. The size of the generated tridiagonal matrix depends upon the number of the smallest eigenvalues to be computed. The result is savings in computations and storage. The block Lanczos algorithm is well -suited for problems involving multiple eigenvalues. In this thesis, we develop the block Lanczos algorithm to estimate the direction-of-arrival (DOA) of a point source based on the observations measured at a linear array of sensors and compare the performance with that of a single vector Lanczos algorithm. The results of the computer simulation experiments conducted with this method are presented and discussed.
dc.description.urihttp://archive.org/details/blocklanczoslgor1094525715
dc.format.extent62 p.en_US
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsCopyright is reserved by the copyright owner
dc.titleBlock Lanczos algorithm.en_US
dc.typeThesisen_US
dc.contributor.secondreaderTherrien, Charles W.
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentElectrical and Computer Engineering
dc.subject.authorsingle vectoren_US
dc.subject.authorblock Lanczosen_US
dc.subject.authorDOAen_US
dc.description.serviceCaptain, Korean Army
etd.thesisdegree.nameM.S. in Electrical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineElectrical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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