Despite its important signal processing applications, the generalized singular value decomposition (GSVD) is under-utilized due to the high updating cost. In this paper, we introduce a new approximate GSVD that is easily amenable to updating.
A New Method for Nonorthogonal Signal Decomposition
โ Scribed by Nikolay Polyak; William A. Pearlman
- Publisher
- Elsevier Science
- Year
- 1994
- Tongue
- English
- Weight
- 538 KB
- Volume
- 5
- Category
- Article
- ISSN
- 1047-3203
No coin nor oath required. For personal study only.
โฆ Synopsis
A new algorithm for nonorthogonal decomposition is proposed and applied to Gabor decomposition of images. The algorithm is iterative and its advantages are discussed. Proof of the convergence of the algorithm is given. Also, a modified version of the algorithm is considered which increases the rate of convergence. Image simulations show that this method gives much lower reconstruction error than the method using biorthogonal functions, at the cost of a greater amount of computer time. O 1994 Academic Press, Inc.
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