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|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 naive 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. (C) 2017 Elsevier Inc. All rights reserved.|
|Electronic Publication Date:||9-Mar-2017|
|Citation:||Zhang, Teng, Singer, Amit. (2017). Disentangling orthogonal matrices. LINEAR ALGEBRA AND ITS APPLICATIONS, 524 (159 - 181. doi:10.1016/j.laa.2017.03.002|
|Pages:||159 - 181|
|Type of Material:||Journal Article|
|Journal/Proceeding Title:||LINEAR ALGEBRA AND ITS APPLICATIONS|
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