Preconditioning Filter Bank Decomposition Using Structured Normalized Tight Frames

We turn a given filter bank into a filtering scheme that provides perfect reconstruction, synthesis is the adjoint of the analysis part (so-called unitary filter banks), all filters have equal norm, and the essential features of the original filter bank are preserved. Unitary filter banks providing...

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Main Author: Martin Ehler
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2015/861563
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spelling doaj-67365527305548df8ddd3ff36d377a982020-11-25T00:24:13ZengHindawi LimitedJournal of Applied Mathematics1110-757X1687-00422015-01-01201510.1155/2015/861563861563Preconditioning Filter Bank Decomposition Using Structured Normalized Tight FramesMartin Ehler0Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, AustriaWe turn a given filter bank into a filtering scheme that provides perfect reconstruction, synthesis is the adjoint of the analysis part (so-called unitary filter banks), all filters have equal norm, and the essential features of the original filter bank are preserved. Unitary filter banks providing perfect reconstruction are induced by tight generalized frames, which enable signal decomposition using a set of linear operators. If, in addition, frame elements have equal norm, then the signal energy is spread through the various filter bank channels in some uniform fashion, which is often more suitable for further signal processing. We start with a given generalized frame whose elements allow for fast matrix vector multiplication, as, for instance, convolution operators, and compute a normalized tight frame, for which signal analysis and synthesis still preserve those fast algorithmic schemes.http://dx.doi.org/10.1155/2015/861563
collection DOAJ
language English
format Article
sources DOAJ
author Martin Ehler
spellingShingle Martin Ehler
Preconditioning Filter Bank Decomposition Using Structured Normalized Tight Frames
Journal of Applied Mathematics
author_facet Martin Ehler
author_sort Martin Ehler
title Preconditioning Filter Bank Decomposition Using Structured Normalized Tight Frames
title_short Preconditioning Filter Bank Decomposition Using Structured Normalized Tight Frames
title_full Preconditioning Filter Bank Decomposition Using Structured Normalized Tight Frames
title_fullStr Preconditioning Filter Bank Decomposition Using Structured Normalized Tight Frames
title_full_unstemmed Preconditioning Filter Bank Decomposition Using Structured Normalized Tight Frames
title_sort preconditioning filter bank decomposition using structured normalized tight frames
publisher Hindawi Limited
series Journal of Applied Mathematics
issn 1110-757X
1687-0042
publishDate 2015-01-01
description We turn a given filter bank into a filtering scheme that provides perfect reconstruction, synthesis is the adjoint of the analysis part (so-called unitary filter banks), all filters have equal norm, and the essential features of the original filter bank are preserved. Unitary filter banks providing perfect reconstruction are induced by tight generalized frames, which enable signal decomposition using a set of linear operators. If, in addition, frame elements have equal norm, then the signal energy is spread through the various filter bank channels in some uniform fashion, which is often more suitable for further signal processing. We start with a given generalized frame whose elements allow for fast matrix vector multiplication, as, for instance, convolution operators, and compute a normalized tight frame, for which signal analysis and synthesis still preserve those fast algorithmic schemes.
url http://dx.doi.org/10.1155/2015/861563
work_keys_str_mv AT martinehler preconditioningfilterbankdecompositionusingstructurednormalizedtightframes
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