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Article
Optimality of Balanced Proper Orthogonal Decomposition for Data Reconstruction
Numerical Functional Analysis and Optimization
  • John R. Singler, Missouri University of Science and Technology
Abstract
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.
Department(s)
Mathematics and Statistics
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2010 Taylor & Francis, All rights reserved.
Publication Date
1-1-2010
Citation Information
John 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/