• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 841
Next 10 →

Morphology-based perfect reconstruction filter banks

by Henk J. A. M. Heijmans - In Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis , 1998
"... This paper discusses the construction of perfect reconstruction filter banks using morphological operators. Two concrete examples are given:   ¢¡¤£ the morphological Haar wavelet, and ¥¡¦¡§ £ a wavelet decomposition obtained from the lifting scheme which has the nice property that local maxima are b ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
This paper discusses the construction of perfect reconstruction filter banks using morphological operators. Two concrete examples are given:   ¢¡¤£ the morphological Haar wavelet, and ¥¡¦¡§ £ a wavelet decomposition obtained from the lifting scheme which has the nice property that local maxima

PERFECT RECONSTRUCTION FILTER BANKS FOR HDTV REPRESENTATION AND CODING

by Martin Vetterli, Didier J. Legall, et al. , 1990
"... Subband decomposition of HDTV signals is important both for representation purposes (to create compatible subchannels) and for coding (several proposed compression schemes include some subband division). We first review perfect reconstruction filter banks in multiple dimensions in the context of a ..."
Abstract - Cited by 15 (0 self) - Add to MetaCart
Subband decomposition of HDTV signals is important both for representation purposes (to create compatible subchannels) and for coding (several proposed compression schemes include some subband division). We first review perfect reconstruction filter banks in multiple dimensions in the context

Signal Extensions in perfect reconstruction Filter Banks

by Joo Silvestre And, João Silvestre, Luís De Sá
"... The Wavelet transform is defined for infinite-length signals. In practice we only have finite-length signals, so signals must be extended before they can be transformed. The question is how to extend the signal to minimize signal end effects, or how to find the signal extension that preserves the tr ..."
Abstract - Add to MetaCart
the transform signal length. In this paper we discuss the problem of signal extension in perfect reconstruction filter banks. 1. INTRODUCTION One key problem in subband and wavelet coding systems, is the decomposition of limited size signals. If we consider the case of an input signal x[n] of even length N

On the Completeness of the Lattice Factorization for Linear-Phase Perfect Reconstruction Filter Banks

by Lu Gan, Kai-kuang Ma, Senior Member, Truong Q. Nguyen, Senior Member, Trac D. Tran, Ricardo L. De Queiroz, Senior Member
"... Abstract—In this letter, we re-examine the completeness of the lattice factorization for-channel linear-phase perfect reconstruction filter bank (LPPRFB) with filters of the same length = in [1]. We point out that the assertion of completeness in [1] is incorrect. Examples are presented to show that ..."
Abstract - Add to MetaCart
Abstract—In this letter, we re-examine the completeness of the lattice factorization for-channel linear-phase perfect reconstruction filter bank (LPPRFB) with filters of the same length = in [1]. We point out that the assertion of completeness in [1] is incorrect. Examples are presented to show

On efficient implementation of oversampled linear phase perfect reconstruction filter banks

by Jie Liang' , Lu Gan2 , Chengjie Tu' , Trac D Tran' , Kai-Kuang Ma2 - in ICASSP 2003 , 2003
"... ABSTRACT In this paper, we first present an alternative way of generating oversampled linear phase perfect reconstruction filter banks (OSLP-PRFB). We show that this method provides the minimal factorization of a subset of existing OSLPPRFB. The combination of the new structure and the conventional ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
ABSTRACT In this paper, we first present an alternative way of generating oversampled linear phase perfect reconstruction filter banks (OSLP-PRFB). We show that this method provides the minimal factorization of a subset of existing OSLPPRFB. The combination of the new structure

THE REPLACEABILITY OF SAMPLING MATRIX FOR MULTIDIMENSIONAL PERFECT RECONSTRUCTION FILTER BANKS

by Bo Yang, Zhongliang Jing , 2008
"... It is shown under a divisibility condition the sampling matrix for a filter bank can be replaced without loss of perfect reconstruction. This is the generalization of the common knowledge that removing up/downsampling will not alter perfect reconstruction. The result provides a simple way to impleme ..."
Abstract - Add to MetaCart
It is shown under a divisibility condition the sampling matrix for a filter bank can be replaced without loss of perfect reconstruction. This is the generalization of the common knowledge that removing up/downsampling will not alter perfect reconstruction. The result provides a simple way

Jordan Representation of Perfect Reconstruction Filter Banks using Nilpotent Matrices

by Asha Vijayakumar, G. Abhilash
"... Abstract: This paper contains the factorization of the polyphase matrix of finite impulse response perfect reconstruction filter banks into unimodular factors containing finite Jordan nilpotent structures and the associated transform matrices. An important contribution of the paper is the proposal o ..."
Abstract - Add to MetaCart
Abstract: This paper contains the factorization of the polyphase matrix of finite impulse response perfect reconstruction filter banks into unimodular factors containing finite Jordan nilpotent structures and the associated transform matrices. An important contribution of the paper is the proposal

Time-Varying Perfect Reconstruction Filter Banks for Finite Length Signals

by Vitor Silva, Luís de Sá , 1998
"... : A new approach to the non-expansive two band decomposition of finite length signals is introduced. The technique is based on the time-varying perfect reconstruction filter banks concept. In this approach the main analysis filter bank is instantaneously switched, at the signal boundaries, to a shor ..."
Abstract - Add to MetaCart
: A new approach to the non-expansive two band decomposition of finite length signals is introduced. The technique is based on the time-varying perfect reconstruction filter banks concept. In this approach the main analysis filter bank is instantaneously switched, at the signal boundaries, to a

NEAR PERFECT RECONSTRUCTION FILTER BANKS FOR POWER QUALITY ANALYSIS

by Dimitar Taskovski
"... The wavelet transform has been successfully used in the area of power quality analysis. There are many published papers with methods for power quality disturbance classification or harmonics measurement, which use wavelet transform. However, the properties of the wavelet transform can drastically va ..."
Abstract - Add to MetaCart
vary from the choice of the wavelet. In this paper we analyze the influence of the choice of the wavelet to the accuracy of the power quality classification method and to high frequency harmonics measurements. Additionally to the well known wavelet filters we introduce near perfect reconstruction

Perfect reconstruction filter banks with rational sampling rate changes

by Jelena Kovacevic, Martin Vetterli, Senior Member - in Proc. IEEE Int. Con$ Acoust., Speech, Signal Processing , 1991
"... Abstract-This paper solves an open problem, namely, how to construct perfect reconstruction filter banks with rational sampling factors. Such filter banks have N branches, each one having a sampling factor of p i / q i and their sum equals to one. In this way, the well-known theory of filter banks w ..."
Abstract - Cited by 45 (0 self) - Add to MetaCart
Abstract-This paper solves an open problem, namely, how to construct perfect reconstruction filter banks with rational sampling factors. Such filter banks have N branches, each one having a sampling factor of p i / q i and their sum equals to one. In this way, the well-known theory of filter banks
Next 10 →
Results 1 - 10 of 841
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University