Disentangling Orthogonal Matrices
Keywords
Cryo-EM; Orthogonal Procrustes problem; SDP relaxation
Abstract
Motivated by a certain molecular reconstruction methodology in cryo-electron microscopy, we consider the problem of solving a linear system with two unknown orthogonal matrices, which is a generalization of the well-known orthogonal Procrustes problem. We propose an algorithm based on a semi-definite programming (SDP) relaxation, and give a theoretical guarantee for its performance. Both theoretically and empirically, the proposed algorithm performs better than the naïve approach of solving the linear system directly without the orthogonal constraints. We also consider the generalization to linear systems with more than two unknown orthogonal matrices.
Publication Date
7-1-2017
Publication Title
Linear Algebra and Its Applications
Volume
524
Number of Pages
159-181
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/j.laa.2017.03.002
Copyright Status
Unknown
Socpus ID
85015645786 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85015645786
STARS Citation
Zhang, Teng and Singer, Amit, "Disentangling Orthogonal Matrices" (2017). Scopus Export 2015-2019. 5323.
https://stars.library.ucf.edu/scopus2015/5323