Designing digital filter banks using wavelets

Abstract In digital filters theory, filtering techniques generally deal with pole-zero structures. In this context, filtering schemes, such as infinite impulse response (IIR) filters, are described by linear differential equations or linear transformations, in which the impulse response of each filt...

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Main Authors: Sergio R. M. Penedo, Marcio Lobo Netto, João F. Justo
Format: Article
Language:English
Published: SpringerOpen 2019-07-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13634-019-0632-6
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spelling doaj-20f2d72df1e743529964f9c1c95d8de92020-11-25T03:02:15ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802019-07-012019111110.1186/s13634-019-0632-6Designing digital filter banks using waveletsSergio R. M. Penedo0Marcio Lobo Netto1João F. Justo2Departamento de Engenharia de Sistemas Eletrônicos, Escola Politécnica, Universidade de São PauloDepartamento de Engenharia de Sistemas Eletrônicos, Escola Politécnica, Universidade de São PauloDepartamento de Engenharia de Sistemas Eletrônicos, Escola Politécnica, Universidade de São PauloAbstract In digital filters theory, filtering techniques generally deal with pole-zero structures. In this context, filtering schemes, such as infinite impulse response (IIR) filters, are described by linear differential equations or linear transformations, in which the impulse response of each filter provides its complete characterization, under filter design specifications. On the other hand, finite impulse response (FIR) digital filters are more flexible than the analog ones, yielding higher quality factors. Since many approaches to the circuit synthesis using the wavelet transform have been recently proposed, here we present a digital filter design algorithm, based on signal wavelet decomposition, which explores the energy partitioning among frequency sub-bands. Exploring such motivation, the method involves the design of a perfect reconstruction wavelet filter bank, of a suitable choice of roots in the Z-plane, through a spectral factorization, exploring the orthogonality and localization property of the wavelet functions. This approach resulted in an energy partitioning across scales of the wavelet transform that enabled a superior filtering performance, in terms of its behavior on the pass and stop bands. This algorithm presented superior results when compared to windowed FIR digital filter design, in terms of the intended behavior in its transition band. Simulations of the filter impulse response for the proposed method are presented, displaying the good behavior of the method with respect to the transition bandwidth of the involved filters.http://link.springer.com/article/10.1186/s13634-019-0632-6FilteringWavelet analysisCircuit synthesis
collection DOAJ
language English
format Article
sources DOAJ
author Sergio R. M. Penedo
Marcio Lobo Netto
João F. Justo
spellingShingle Sergio R. M. Penedo
Marcio Lobo Netto
João F. Justo
Designing digital filter banks using wavelets
EURASIP Journal on Advances in Signal Processing
Filtering
Wavelet analysis
Circuit synthesis
author_facet Sergio R. M. Penedo
Marcio Lobo Netto
João F. Justo
author_sort Sergio R. M. Penedo
title Designing digital filter banks using wavelets
title_short Designing digital filter banks using wavelets
title_full Designing digital filter banks using wavelets
title_fullStr Designing digital filter banks using wavelets
title_full_unstemmed Designing digital filter banks using wavelets
title_sort designing digital filter banks using wavelets
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6180
publishDate 2019-07-01
description Abstract In digital filters theory, filtering techniques generally deal with pole-zero structures. In this context, filtering schemes, such as infinite impulse response (IIR) filters, are described by linear differential equations or linear transformations, in which the impulse response of each filter provides its complete characterization, under filter design specifications. On the other hand, finite impulse response (FIR) digital filters are more flexible than the analog ones, yielding higher quality factors. Since many approaches to the circuit synthesis using the wavelet transform have been recently proposed, here we present a digital filter design algorithm, based on signal wavelet decomposition, which explores the energy partitioning among frequency sub-bands. Exploring such motivation, the method involves the design of a perfect reconstruction wavelet filter bank, of a suitable choice of roots in the Z-plane, through a spectral factorization, exploring the orthogonality and localization property of the wavelet functions. This approach resulted in an energy partitioning across scales of the wavelet transform that enabled a superior filtering performance, in terms of its behavior on the pass and stop bands. This algorithm presented superior results when compared to windowed FIR digital filter design, in terms of the intended behavior in its transition band. Simulations of the filter impulse response for the proposed method are presented, displaying the good behavior of the method with respect to the transition bandwidth of the involved filters.
topic Filtering
Wavelet analysis
Circuit synthesis
url http://link.springer.com/article/10.1186/s13634-019-0632-6
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