Systolic Implementations of Up/Down-dating Cholesky Factorization Using Vectorized Gram-Schmidt Pseudo Orthogonalization

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dc.contributor.authorHsieh, S.F.en_US
dc.contributor.authorLiu, K.J. Rayen_US
dc.contributor.authorYao, K.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:47:34Z
dc.date.available2007-05-23T09:47:34Z
dc.date.issued1991en_US
dc.description.abstractWe propose a new class of hyperbolic Gram-Schmidt methods to simultaneously update and downdate the Cholesky factor of a sample covariance matrix efficiently with applications to sliding window recursive least squares (RLS) filtering problems. Several vectorized versions of this Gram-Schmidt approach are introduced, which include conventional column-updating, modified row/column- updating, and square-root-free methods. Comparisons to the existing known methods, such as Householder transformation and Givens rotation, are also given. Upon further reformulating these algorithms, a systolic triarray structure is proposed to facilitate VLSI implementations.en_US
dc.format.extent682606 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5072
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1991-23en_US
dc.subjectsignal processingen_US
dc.subjectalgorithmsen_US
dc.subjectparallel architecturesen_US
dc.subjectVLSI architecturesen_US
dc.subjectSystems Integrationen_US
dc.titleSystolic Implementations of Up/Down-dating Cholesky Factorization Using Vectorized Gram-Schmidt Pseudo Orthogonalizationen_US
dc.typeTechnical Reporten_US

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