Inferring the eigenvalues of covariance matrices from limited, noisy data

Bibliographic Details
Main Authors: Everson, R, Roberts, S
Format: Journal article
Published: 2000
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author Everson, R
Roberts, S
author_facet Everson, R
Roberts, S
author_sort Everson, R
collection OXFORD
description
first_indexed 2024-03-07T05:46:45Z
format Journal article
id oxford-uuid:e778db22-e8fc-4a8b-86fe-3a816df68c30
institution University of Oxford
last_indexed 2024-03-07T05:46:45Z
publishDate 2000
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spelling oxford-uuid:e778db22-e8fc-4a8b-86fe-3a816df68c302022-03-27T10:38:59ZInferring the eigenvalues of covariance matrices from limited, noisy dataJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e778db22-e8fc-4a8b-86fe-3a816df68c30Symplectic Elements at Oxford2000Everson, RRoberts, S
spellingShingle Everson, R
Roberts, S
Inferring the eigenvalues of covariance matrices from limited, noisy data
title Inferring the eigenvalues of covariance matrices from limited, noisy data
title_full Inferring the eigenvalues of covariance matrices from limited, noisy data
title_fullStr Inferring the eigenvalues of covariance matrices from limited, noisy data
title_full_unstemmed Inferring the eigenvalues of covariance matrices from limited, noisy data
title_short Inferring the eigenvalues of covariance matrices from limited, noisy data
title_sort inferring the eigenvalues of covariance matrices from limited noisy data
work_keys_str_mv AT eversonr inferringtheeigenvaluesofcovariancematricesfromlimitednoisydata
AT robertss inferringtheeigenvaluesofcovariancematricesfromlimitednoisydata