1996
DOI: 10.1006/acha.1996.0026
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Classification of Nonexpansive Symmetric Extension Transforms for Multirate Filter Banks

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Cited by 109 publications
(51 citation statements)
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“…Hence, we can write the basis functions for the FRIT as follows: (27) We can next prove the result on the orthogonality of a modified FRIT.…”
Section: Orthonormal Finite Ridgelet Transformmentioning
confidence: 99%
See 1 more Smart Citation
“…Hence, we can write the basis functions for the FRIT as follows: (27) We can next prove the result on the orthogonality of a modified FRIT.…”
Section: Orthonormal Finite Ridgelet Transformmentioning
confidence: 99%
“…, , that satisfy the Condition then is an orthonormal basis in , where are defined in (27) and is the constant function, , .…”
Section: Orthonormal Finite Ridgelet Transformmentioning
confidence: 99%
“…In the literature are suggests the following extension method the series (Hadaś-Dyduch, 2014b, 2017Brislawn, 1996;Cohen, Daubechies, & Jawerth, 1993;Strang & Nguyen, 1996;Nason & Silverman, 1995):…”
Section: Extending Of the Time Seriesmentioning
confidence: 99%
“…Application of wavelet transforms to finite-length signals and, in particular, to images, requires an extension of signals beyond their boundaries [8]. The extension is even more important in our scheme since we implicitly assumed in our construction that the signals are defined on infinite intervals.…”
Section: Appendix I Implementation Of Recursive Filtersmentioning
confidence: 99%
“…The extension is even more important in our scheme since we implicitly assumed in our construction that the signals are defined on infinite intervals. When the filter banks are symmetric, the extension in the terminology of [8] is most efficient. It means that the signal , is symmetrically extended with the repetition of boundary samples through both ends of the interval.…”
Section: Appendix I Implementation Of Recursive Filtersmentioning
confidence: 99%