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.
Original language | English (US) |
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Pages (from-to) | 159-181 |
Number of pages | 23 |
Journal | Linear Algebra and Its Applications |
Volume | 524 |
DOIs | |
State | Published - Jul 1 2017 |
All Science Journal Classification (ASJC) codes
- Discrete Mathematics and Combinatorics
- Geometry and Topology
- Numerical Analysis
- Algebra and Number Theory
Keywords
- Cryo-EM
- Orthogonal Procrustes problem
- SDP relaxation