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HETEROGENEOUS MULTIREFERENCE ALIGNMENT: A SINGLE PASS APPROACH

Author(s): Boumal, Nicolas; Bendory, Tamir; Lederman, Roy R; Singer, Amit

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dc.contributor.authorBoumal, Nicolas-
dc.contributor.authorBendory, Tamir-
dc.contributor.authorLederman, Roy R-
dc.contributor.authorSinger, Amit-
dc.date.accessioned2018-07-20T15:07:41Z-
dc.date.available2018-07-20T15:07:41Z-
dc.date.issued2018en_US
dc.identifier.citationBoumal, Nicolas, Bendory, Tamir, Lederman, Roy R, Singer, Amit. (2018). HETEROGENEOUS MULTIREFERENCE ALIGNMENT: A SINGLE PASS APPROACH. 2018 52ND ANNUAL CONFERENCE ON INFORMATION SCIENCES AND SYSTEMS (CISS)en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1r37b-
dc.description.abstractMultireference alignment (MRA) is the problem of estimating a signal from many noisy and cyclically shifted copies of itself. In this paper, we consider an extension called heterogeneous MRA, where K signals must be estimated, and each observation comes from one of those signals, unknown to us. This is a simplified model for the heterogeneity problem notably arising in cryo-electron microscopy. We propose an algorithm which estimates theK signals without estimating either the shifts or the classes of the observations. It requires only one pass over the data and is based on low-order moments that are invariant under cyclic shifts. Given sufficiently many measurements, one can estimate these invariant features averaged over the K signals. We then design a smooth, non-convex optimization problem to compute a set of signals which are consistent with the estimated averaged features. We find that, in many cases, the proposed approach estimates the set of signals accurately despite non-convexity, and conjecture the number of signals K that can be resolved as a function of the signal length L is on the order of root L.en_US
dc.language.isoen_USen_US
dc.relation.ispartof2018 52ND ANNUAL CONFERENCE ON INFORMATION SCIENCES AND SYSTEMS (CISS)en_US
dc.rightsAuthor's manuscripten_US
dc.titleHETEROGENEOUS MULTIREFERENCE ALIGNMENT: A SINGLE PASS APPROACHen_US
dc.typeConference Articleen_US
dc.date.eissued2018-05-24en_US
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/conference-proceedingen_US

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