Optimality of Balanced Proper Orthogonal Decomposition for Data ReconstructionNumerical Functional Analysis and Optimization
AbstractProper 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.
Department(s)Mathematics and Statistics
Document TypeArticle - Journal
Document VersionFinal Version
Rights© 2010 Taylor & Francis, All rights reserved.
Citation InformationJohn R. Singler. "Optimality of Balanced Proper Orthogonal Decomposition for Data Reconstruction" Numerical Functional Analysis and Optimization (2010)
Available at: http://works.bepress.com/john-singler/34/