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Singular Value Decomposition (view source)

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'''Singular value decomposition'', or SVD, consists of the reduction of a [[singular matrix]] into the product of orthogonal and square matrices.
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'''Singular value decomposition''', or SVD, consists of the reduction of a [[singular matrix]] into the product of orthogonal and square matrices.
    
Discovered in the 19th century, this technique has recently discovered applications in signal error-reduction and in [[watermarking]].
 
Discovered in the 19th century, this technique has recently discovered applications in signal error-reduction and in [[watermarking]].
 
[[Category:mathematics]]
 
[[Category:mathematics]]
 
[[Category:linear algebra]]
 
[[Category:linear algebra]]
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