Abstract
Using the projection theorem in a Hilbert space, the quotient singular value decomposition (QSVD) and the canonical correlation decomposition (CCD) in matrix theory for efficient tools, we obtained the explicit analytical expressions of the optimal approximation solutions for the symmetric and skew-symmetric least-squares problems of the linear matrix equation . This can lead to new algorithms to solve such problems.
Original language | English (US) |
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Title of host publication | Numerical Linear Algebra in Signals, Systems and Control |
Pages | 201-215 |
Number of pages | 15 |
DOIs | |
State | Published - 2011 |
Event | International Workshop on Numerical Linear Algebra in Signal, Systems, and Control - Kharagpur, India Duration: Jan 9 2007 → Jan 11 2007 |
Publication series
Name | Lecture Notes in Electrical Engineering |
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Volume | 80 LNEE |
ISSN (Print) | 1876-1100 |
ISSN (Electronic) | 1876-1119 |
Other
Other | International Workshop on Numerical Linear Algebra in Signal, Systems, and Control |
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Country/Territory | India |
City | Kharagpur |
Period | 1/9/07 → 1/11/07 |
Bibliographical note
Funding Information:The author Deng would like to thank the China Scholarship Council for providing the State Scholarship Fund to pursue his research at the University of Minnesota as a visiting scholar. The author Boley would like to acknowledge partial support for this research from NSF grant IIS-0916750.
Keywords
- CCD
- Least-squares problem (Procrustes problem)
- Linear matrix equation
- Optimal approximation solution
- QSVD