DocumentCode :
1554055
Title :
SVD compression, unitary transforms, and computational complexity
Author :
Knockaert, Luc ; De Backer, Bernard ; De Zutter, Daniël
Author_Institution :
INTEC, Ghent, Belgium
Volume :
47
Issue :
10
fYear :
1999
fDate :
10/1/1999 12:00:00 AM
Firstpage :
2724
Lastpage :
2729
Abstract :
The search for fast unitary transforms and the need for data compression in linear systems are complementary issues. Compression requires the definition of a threshold dependent on the condition number, which is invariant over the unitary group. With respect to this threshold, it is shown that the SVD is the optimal tool. Considerations in connection with the Kronecker product and direct sum of unitary matrices show that the computational complexity of unitary transforms is entropy-like in nature, thereby indicating that the O(n log n) complexity unitary transforms are dense over the unitary group
Keywords :
computational complexity; data compression; linear systems; singular value decomposition; transforms; Kronecker product; SVD compression; computational complexity; condition number; data compression; linear systems; threshold; unitary matrices; unitary transforms; Complexity theory; Computational complexity; Data compression; Entropy; Helium; Linear systems; Matrix decomposition; Signal processing algorithms; Singular value decomposition; Working environment noise;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.790654
Filename :
790654
Link To Document :
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