Proper orthogonal decomposition (POD) finds an orthonormal basis yielding an optimal reconstruction of a given dataset. We consider an optimal data reconstruction problem for two general datasets related to balanced POD, which is an algorithm for balanced truncation model reduction for linear systems. We consider balanced POD outside of the linear systems framework, and prove that it solves the optimal data reconstruction problem. the theoretical result is illustrated with an example.
J. R. Singler, "Optimality of Balanced Proper Orthogonal Decomposition for Data Reconstruction," Numerical Functional Analysis and Optimization, Taylor & Francis, Jan 2010.
The definitive version is available at http://dx.doi.org/10.1080/01630563.2010.500022
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