Wavelet Digest, Vol. 07, Nr. 10.
Ken Jackson
Wavelet Digest Friday, October 16, 1998 Volume 7 : Issue 10
Today's Editor: Wim Sweldens
Lucent Technologies, Bell Laboratories
w...@bell-labs.com
Your e-mail address: k...@cs.toronto.edu
Today's Topics:
1. Preprint: Commutation for Irregular Subdivision
2. Preprint: Reconstruct 2D Mother Wavelet from 1D Projections
3. Preprint: Automatic Phase Detection in Seismic Data using the DWT
4. Preprint: Translation-invariant denoising from I. Cohen et al.
5. Preprint: A New Image Compression Algorithm (HEP Algorithm)
6. Preprint: Adaptive Wavelet Synthesis
7. Preprint: Compactly Supported Refinable Functions with Infinite Masks
8. Preprint: Data analysis of ECN signal with WT
9. Thesis: Shift-Invariant Adaptive Wavelet Decompositions
10. Thesis: Wavelets and Lattice Field Theory (in German)
11. Thesis: Assessing Nonstationary Time Series Using Wavelets
12. Dissertation: Wavelet-based volume rendering
13. Web: JoCAAA Web page
14. Meeting: Wavelet Workshop Dec 16-18 in Houston
15. Meeting: Workshop on Wavelets in Biomedicine
16. Meeting: Mathtools 99, St-Petersburg
17. Meeting: Fractals in Engineering, Delft
18. Meeting: SPIE Wavelet Applications VII
19. Course: Mathematical & Physical Wavelets
20. Job: PhD Fellowships at Polytechnic University - Brooklyn
21. Job: Research Associate, University of Bristol
22. Contents: Numerical Algorithms 18-1
23. Answer: Wavelets in fault diagnsosis (WD 7.9 #19)
24. Question: Seismic data compression
25. Question: Calling all Quincunx wavelet filters
26. Question: Orthogonalizing a non-orthogonal family of wavelets?
27. Question: Wavelet compression of satellite attitude
28. Question: Wavelets' role in Pattern recognition
29. Question: Few problems using wavelet network for vibration transients
Current number of members: 12400
E-mail:
General help: he...@wavelet.org
Add yourself as a member: a...@wavelet.org
Remove yourself as a member: rem...@wavelet.org
Publish in the next WD: pub...@wavelet.org
Receive publishing policy: pol...@wavelet.org
Visit us on the Web at http://www.wavelet.org/
Calendar of events:
Oct 27-28: Wavelets in Biology and Medicine, Hong Kong WD 7.5 #14
Oct 28-29: Workshop and Seminars on Wavelets in Tokyo, Japan WD 7.8 #11
Nov 1: Course Multiscale Image, Champaign, IL WD 7.9 #7
*Dec 16-18: Wavelet Workshop, Houston, TX WD 7.10 #14
*Dec 21-22: Workshop on Wavelets in Biomedicine, Signapore WD 7.10 #15
---
Jan 13-16: Introduction to Wavelets minicourse, San Antonio TX WD 7.9 #8
Feb 24-25: Royal Society London, UK WD 7.5 #13
Feb 24-26: IEEE Information Theory Workshop, Santa Fe, NM WD 7.5 #15
Mar 22-26: II Symposium on Artificial Intelligence, Havana, Cuba WD 7.6 #14
*Jun 14-19: Mathtools 99, St-Petersburg, Russia WD 7.10 #16
*Jun 14-16: Fractals in Engineering, Delft, The Netherlands WD 7.10 #17
Jul 1-7: Curves and Surfaces, St-Malo, France WD 7.5 #12
*Jul 18-23: SPIE Wavelet Applications VII, Denver, CO WD 7.10 #18
----------------------------------------------------------------------
Date: Sat, 19 Sep 1998 13:49:45 -0400
From: "Wim Sweldens" <wim>
Subject: #1 Preprint: Commutation for Irregular Subdivision
Title: Commutation for Irregular Subdivision
Authors: Ingrid Daubechies, Princeton Univ.
Igor Guskov, Princeton Univ.
Wim Sweldens, Lucent Technologies Bell Labs
Abstract:
We present a generalization of Lemarie's commutation formula to
irregular subdivision schemes and wavelets. We show how in the
non-interpolating case the divided differences need to be adapted to
the subdivision scheme. As an example we include the construction of
an entire family of biorthogonal compactly supported irregular knot
B-spline wavelets starting from Lagrangian interpolation
Status: Preprint, Lucent Technologies, Bell Laboratories, 1998
You can download a copy at:
http://cm.bell-labs.com/who/wim/papers/commut/
Note: This paper is a follow-up from an earlier paper "Regularity of
Irregular Subdivision.''
------------------------------
Date: Fri, 25 Sep 1998 10:34:04 +0800
From: app...@cqu.edu.cn
Subject: #2 Preprint: Reconstruct 2D Mother Wavelet from 1D Projections
Author :
Name: Li Zeng, associate professor
Address: Dept. of applied math., Chongqing University, 400044, P.R.China .
phone: 86-23-65106037 E-mail : app...@cqu.edu.cn
Degree: Ph.D. Major: Theory and application of computer science.
Abstract:
Now, wavelet analysis has been applied on 2D image process. For
example, it has been applied on image press, edge detection and noise
filter et. . In 2D wavelet analysis , the construction of 2D mother
wavelet is important and difficult. Some scientists have make some
works. For example, Mallat raised product of tensor construction
method. Long Rui-Ling given direct construction method. Wickerhauser
made mutildimensional library trees, et. . They concern the mother
wavelet which can construct orthogonal basis. But, in fact, there are
some 1D mother wavelets which can not construct orthogonal basis.. For
example , 1D spline mother wavelets. These mother wavelets have been
applied on detection breakdown and filter noise of 1D signal,et.. How
to construct 2D mother wavelet from non-orthogonal 1D mother wavelet,
is the question we try to resolve. In this paper, we construct 2D
mother wavelet from the invert projection of 1D mother wavelet. Thus,
we give another way to construct 2D mother wavelet . This nmethod suit
to construct 2D mother wavelet from non-orthogonal 1D mother wavelet.
By this method, we can construct 3D or ND mother wavelet. By this
method, we can construct 2D mother wavelet which can be applied on
detection breakdown and filter noise of 2D signal, et.
------------------------------
Date: Tue, 29 Sep 1998 13:39:10 +0200
From: patricko <patrick...@cwi.nl>
Subject: #3 Preprint: Automatic Phase Detection in Seismic Data using the DWT
Title: Automatic Phase Detection in Seismic Data using the DWT
Author: Patrick Oonincx
Abstract: Seismic data consist of traces, which contain information
about a seismic event, but in some period of time the traces may be
just noise. A trace which contains seismic information, is called a
seismic signal. Seismic signals consist of several typically short
energy bursts,called phases, exhibiting several patterns in terms of
dominant frequency, amplitude and polarisation. Amongst others, a
significant phase is the S-phase. We present a fast algorithm to
detect the S-phase in a three-component seismic signal. This new
approach is a combination of traditional S-phase detection methods
from seismology and the discrete wavelet transform. Stability and
correctness of the algorithm will be proved and results will be
presented to demonstrate the algorithm.
This preprint and other papers on wavelets can be retrieved from my
homepage
------------------------------
Date: Tue, 29 Sep 1998 15:33:30 -0400
From: Israel Cohen <cohen-...@cs.yale.edu>
Subject: #4 Preprint: Translation-invariant denoising from I. Cohen et al.
Preprints on translation-invariant denoising and robust
time-frequency representations:
1) Adaptive Suppression of Wigner Interference-Terms
Using Shift-Invariant Wavelet Packet Decompositions
Israel Cohen, Shalom Raz and David Malah
Department of Electrical Engineering
Technion - Israel Institute of Technology
Haifa 32000, Israel
Abstract:
The Wigner distribution (WD) possesses a number of desirable
mathematical properties relevant to time-frequency analysis. However,
the presence of interference terms renders the WD of multicomponent
signals extremely difficult to interpret. In this work, we propose
adaptive suppression of interference terms using the {\it
Shift-Invariant Wavelet Packet Decomposition}. A prescribed signal is
expanded on its best basis and transformed into the Wigner
domain. Subsequently, the interference terms are eliminated by
adaptively thresholding the cross WD of interactive basis functions,
according to their amplitudes and distance in an idealized
time-frequency plane. We define a distance measure that weighs the
Euclidean distance with the local distribution of the signal. The
amplitude and distance thresholds control the cross-term interference,
the useful properties of the distribution, and the computational
complexity. The properties of the resultant {\em modified Wigner
distribution\/} (MWD) are investigated, and its performance in
eliminating interference terms, while still retaining high energy
resolution, is compared with that of other existing approaches. It is
shown that the proposed MWD is directly applicable to resolving
multicomponent signals. Each component is determined as a partial sum
of basis-functions over a certain equivalence class in the
time-frequency plane.
Keywords: Shift-invariance; Best-basis; Wavelets; Wavelet-packets;
Wigner distribution; Time-frequency; Interference terms
Technical Report, CC PUB No. 245, Technion - Israel Institute of
Technology, Haifa, Israel, June 1998 (to appear in Signal Processing).
http://www-sipl.technion.ac.il/wavelet.html
2) Translation-invariant denoising using the minimum description
length criterion
Israel Cohen, Shalom Raz and David Malah
Department of Electrical Engineering
Technion - Israel Institute of Technology
Haifa 32000, Israel
Abstract:
A translation-invariant denoising method, based on the {\it Minimum
Description Length\/} (MDL) criterion and tree-structured best-basis
algorithms is presented. A collection of signal models is generated
using an {\it extended\/} library of orthonormal wavelet-packet bases,
and an additive cost function, approximately representing the MDL
principle, is derived. We show that the minimum description length of
the noisy observed data is achieved by utilizing the {\it
Shift-Invariant Wavelet Packet Decomposition\/} (SIWPD) and
thresholding the resulting coefficients. This approach is extendable
to local trigonometric decompositions, and corresponding procedures to
optimize either the library of bases or the filter banks used at each
node of the expansion-tree are described. The signal estimator is
efficiently combined with a {\it modified Wigner distribution\/},
yielding robust time-frequency representations, characterized by high
resolution and suppressed interference-terms. The proposed method is
compared to alternative existing methods, and its superiority is
demonstrated by synthetic and real data examples.
Technical Report, CC PUB No. 246, Technion - Israel Institute of Technology,
Haifa, Israel, June 1998 (submitted to Signal Processing).
http://www-sipl.technion.ac.il/wavelet.html
Dr. Israel Cohen cohen-...@cs.yale.edu
Yale University Tel: +(203) 432-1287
Department of Computer Science Fax: +(203) 432-0593
P.O. Box 208285
New Haven, CT 06520-8285
------------------------------
Date: Wed, 30 Sep 1998 10:27:58 +0800
From: lxj <l...@ns.glc.cn.net>
Subject: #5 Preprint: A New Image Compression Algorithm (HEP Algorithm)
A New Image Compression Algorithm (HEP Algorithm)
ABSTRACT We know JPEG is faster than Wavelet transform algorithm, but
its fidelity is poorer than Wavelet's. As an international standard,
JPEG/MPEG is widely applied in multimedia fields. In recent years,
several new image codings based on WT have been presented, such as
EZW, HARC, SPIHT et al., these schemes can get better fidelity, but
very slow. If there is a method to combine their benefits, we can get
better fidelity and faster speed. HEP algorithm is doing so. HEP is
based on DCT and WT coding scheme, it is faster than WT coding and
better fidelity than JPEG's. The following results are based on HEP
algorithm.
TEST image : LENNA 512*512*8bit
HEP JPEG EZW
CR PSNR(dB) PSNR(dB) CR PSNR(dB)
4.4 42.8 40.9 4.0 44.8
8.4 39.0 37.7 8.0 39.6
15.5 35.8 34.7 16.0 36.3
28.8 32.7 31.2 32.0 33.2
55.2 29.5 24.8 64.0 30.3
106 26.0 -- 128.0 27.5
HEP is over twice as fast as EZW, in addition, the subject evaluation is
better than EZW. There is no blur, no block effects.
Now a new image/speech recognition method based on HEP is been studying
in my research, the primary results manifest that HEP algorithm is very
effective.
------------------------------
Date: Mon, 05 Oct 98 11:59:41 -0500
From: "L.Novikov" <n...@iai.rssi.ru>
Subject: #6 Preprint: Adaptive Wavelet Synthesis
Dear sir,
I would like to include my paper submitted to the 1st International
Conference "Digital Signal Processing and its Applications - DSPA-98", 30
June - 3 July, 1998, Moscow, Russia.
Author L. Novikov
"Adaptive Wavelet Synthesis", DSPA-98 Proceedings, Moscow, 1998.
Abstract: Unlike traditional approaches to synthesis of wavelet bases
the proposed method uses a priori information on the signal shape and
noise correlation function to adapt the wavelet analysis for
experimental conditions. This helps to minimize the effect of noise on
the results of signal analysis and to enhance measurement reliability.
A ps file is it
http://www.iai.rssi.ru/novik/UDK6213.ps
Thank you
------------------------------
From: Vasily Strela <str...@emmy.dartmouth.edu>
Subject: #7 Preprint: Compactly Supported Refinable Functions with Infinite Masks
Title: Compactly Supported Refinable Functions with Infinite Masks
Authors: Gilbert Strang, Vasily Strela, and Ding-Xuan Zhou
Abstract: A compactly supported scaling function can come from a
refinement equation with infinitely many nonzero coefficients (an
infinite mask). In this case we prove that the symbol of the mask
must have the special rational form $\tilde a(Z)=\tilde b(Z^2) \tilde
c(Z)/\tilde b(Z)$. Any finite combination of the shifts of a
refinable function will have such a mask, and will be refinable.
We also study compactly supported solutions of vector refinement
equations with infinite masks. Our characterization is based on the
two-scale similarity transform which plays an essential role in the
investigation of multiple wavelets. This concept is used to
characterize refinable subspaces of refinable shift-invariant spaces.
One advantage of our approach is to provide the refinement masks
for generators of refinable subspaces.
Tha paper can be found at
http://pascal.dartmouth.edu/~strela
or
http://www-math.mit.edu/~gs
------------------------------
Date: Mon, 12 Oct 1998 14:59:30 +0800 (CST)
From: Zhang Maoshen <msz...@dchp.chp.ustc.edu.cn>
Subject: #8 Preprint: Data analysis of ECN signal with WT
Authors & address Ding Hong-bo, Cai Wen-sheng and Pan Zhong-xiao(Dept. of
Applied Chemistry,University of Science & Technology of
China,Hefei,230026,P.R.China)Yu Xin-zeng(Fujian Institute of Research on
the structure of Matters,Chinese Academy of Sciences,Xiamen,361012)
Keyword Continuous WT,phase plane, ECN ,Concrete reinforced steel
Paper one: "ECN" Signal and Wavelet Transform(Review Work)
Because of the simplicity of testing appliance,ECN method has
attracted much attention on the field of electrochemistry,especially
the monitoring of metal corrosion.Due to the unstationary nature of
ECN signal,the data analysis has been a hard barrier for the wide use
of this technology.We pointed out that,based on the time-frequency
characteristic,wavelet transform will be an ideal tool to solve this
kind of problem.We also implied that,"WT & ECN" will be a promising
method in the study of electrochemical dynamics.
Paper Two:
The Analysis of ECN signal with Continuous Wavelet
Transform(practical work)
Continuous Wavelet Transform was employed to transfer the original ECN
signal into a time-frequency phase plane with colors representing the
coefficiences of CWT.Thus,the time-frequency characteristic of ECN
signal concerning the corrosion process of concrete reinforced steel
was vividly manifested.From the phase plane,we can differenciate the
general corrosion and localized ones.
My email hbd...@263.net
------------------------------
Date: Tue, 29 Sep 1998 15:36:16 -0400
From: Israel Cohen <cohen-...@cs.yale.edu>
Subject: #9 Thesis: Shift-Invariant Adaptive Wavelet Decompositions
Title: Shift-Invariant Adaptive Wavelet Decompositions and Applications
D.Sc. Dissertation, Technion - Israel Institute of
Technology, Haifa, Israel, May~1998.
Author: Israel Cohen
Supervisors: Prof. Shalom Raz and Prof. David Malah
Abstract:
Adaptive representations in libraries of bases, including the
wavelet-packet and local trigonometric decompositions, are widely used
in various applications. A major drawback restricting their use,
particularly in statistical signal processing applications, such as
detection, identification or noise removal (denoising), is the lack of
shift-invariance. The expansion, as well as the information cost
measuring its suitability for a particular application, may be
significantly influenced by the alignment of the input signal with
respect to the basis functions. Furthermore, the time-frequency
tilings, produced by the best-basis expansions, do not generally
conform to standard time-frequency energy distributions.
The objective of this work is to develop a general approach for
achieving shift-invariance, enhanced time-frequency decompositions and
robust signal estimators using libraries of orthonormal bases. The
first problem we address is that of shift-invariant adaptive
decompositions in libraries of wavelet packet and local trigonometric
bases. We introduce shift-invariant decompositions that are
characterized by lower information cost, improved time-frequency
resolution, and for a prescribed data set yield more stable cost
functions. The computational complexities are investigated, and
efficient procedures for their control at the expense of the attained
information cost are presented.
A second issue, closely related to the problem of shift-invariance, is
that of adaptive decompositions of time-frequency distributions and
removal of interference terms associated with bilinear
distributions. We show that utilizing the shift-invariant
decompositions, various useful properties relevant to time-frequency
analysis, including high energy concentration and suppressed
interference terms, can be achieved simultaneously in the Wigner
domain. Instead of smoothing, which broadens the energy distribution
of signal components, we propose cross-term manipulations that are
adapted to the local distribution of the signal. The properties of the
resultant modified Wigner distribution are investigated, and its
distinctive applicability to resolving multicomponent signals is
demonstrated.
The final topic concerns the problem of translation-invariant
denoising, using the Minimum Description Length (MDL) criterion. We
define a collection of signal models based on an extended library of
orthonormal bases, and apply the MDL principle to derive an
approximate additive cost function. The description length of the
noisy observed data is then minimized by optimizing the expansion-tree
associated with the best-basis algorithm and thresholding the
resulting coefficients. We show that the signal estimator can be
efficiently combined with the modified Wigner distribution, yielnding
robust time-frequency representations. The proposed methods are
compared to alternative existing methods, and their superiority is
demonstrated by synthetic and real data examples.
Contents:
Chapter 1 Introduction
Chapter 2 Shift-Invariant Wavelet Packet Decompositions
Chapter 3 Shift-Invariant Trigonometric Decompositions
Chapter 4 Adaptive Time-Frequency Distributions
Chapter 5 Translation-Invariant Denoising
Chapter 6 Conclusion
The thesis is available at:
http://www-sipl.technion.ac.il/wavelet.html
Dr. Israel Cohen cohen-...@cs.yale.edu
Yale University Tel: +(203) 432-1287
Department of Computer Science Fax: +(203) 432-0593
P.O. Box 208285
New Haven, CT 06520-8285
------------------------------
Date: Wed, 30 Sep 1998 12:23:46 +0200 (MSZ)
From: Christoph Best <be...@zib.de>
Subject: #10 Thesis: Wavelets and Lattice Field Theory (in German)
Recently, I completed my Ph.D. thesis on "Modern numerical methods for
field theories on the lattice" at the Institute for Theoretical
Physics, J. W. Goethe University, Frankfurt, Germany.
It includes two chapters on
1. "Wavelet Analysis of the Landau-Ginzburg Theory" and
2. "Approximate Solution of Hamiltonian Lattice Gauge Theory
in Wavelet Space"
*Unfortunately, it is currently only available in German.*
Summaries for the two chapters:
1. The application of the Wavelet transformation to the
Landau-Ginzburg theory of critical phenomena is investigated. It
is shown that the Wavelet transformation can be viewed as a
realization of the renormalization group. Renormalization flow is
investigated in the framework of a simple variational
approximation.
2. The wavelet transform is applied to a particularly simple variant of
Hamiltonian lattice gauge theory. It is investigated how the
wavelet space can be used to truncate the field equations and
derive a qualitative picture of the effective equations of
motions.
It can be downloaded from:
http://www.zib.de/best/diss.ps.gz
Christoph Best be...@zib.de
Konrad-Zuse-Zentrum fuer Informationstechnik http://www.zib.de/best
Takustrasse 7, 14195 Berlin, Germany +49-(0)30-84185-216, Fax -107
------------------------------
Date: Mon, 12 Oct 1998 15:10:00 +0200
From: "Whitcher, B." <whit...@eurandom.tue.nl>
Subject: #11 Thesis: Assessing Nonstationary Time Series Using Wavelets
In July 1998 I finished my thesis concerning wavelet analysis of
nonstationary time series with application to the physical sciences.
With respect to univariate time series, I investigated the ability to
detect and locate changes of variance (single and multiple) in time
series with long-range dependence; i.e., slowly decaying
autocorrelations. This is done on a scale by scale basis using output
from the discrete wavelet transform (both orthogonal and
translation-invariant).
I extend the notion of analysis of variance in time series by
considering the analysis of covariance between bivariate time series.
The concepts of wavelet cross-covariance and cross-correlation are
intuitively defined. The basic property that the wavelet covariance
decomposes the process covariance on a scale by scale basis is proved,
and confidence intervals for estimators of these quantities are
established.
Examples taken from the physical sciences include:
Nile River minimum water levels (Toussoun 1925),
vertical ocean shear measurements (Percival and Guttorp 1994),
the Southern Oscillation Index (Walker 1928), and
the Madden-Julian oscillation (Madden and Julian 1971).
The entire thesis may be downloaded from
http://www.eurandom.tue.nl/whitcher/papers/
and the abstract is as follows:
The discrete wavelet transform has be used extensively in the field of
statistics, mostly in the area of "denoising signals" or nonparametric
regression. This thesis provides a new application for the discrete
wavelet transform, assessing nonstationary events in time series --
especially long memory processes. Long memory processes are those
which exhibit substantial correlations between events separated by a
long period of time.
Departures from stationarity in these heavily autocorrelated time
series, such as an abrupt change in the variance at an unknown
location or "bursts" of increased variability, can be detected and
accurately located using discrete wavelet transforms -- both
orthogonal and overcomplete. A cumulative sum of squares method,
utilizing a Kolomogorov--Smirnov-type test statistic, and an
information criterion method are investigated. By analyzing a time
series on a scale by scale basis, each scale corresponding to a range
of frequencies, the ability to detect and locate a sudden change in
the variance in the time series is introduced. Using this same
procedure to detect a change in the long memory parameter is also
investigated. Applications involve the Nile River minimum water
levels and vertical ocean shear measurements.20
In the atmospheric sciences, broadband features in the spectrum of
recorded time series have been hypothesized to be nonstationary
events; e.g., the Madden--Julian oscillation. The Madden--Julian
oscillation is a result of large-scale circulation cells oriented in
the equatorial plane from the Indean Ocean to the central Pacific. The
oscillation has been noted to have higher frequencies during warm
events in El NiF1o--Southern Oscillation (ENSO) years. The concepts of
wavelet covariance and wavelet correlation are introduced and applied
to this problem as an alternative to cross-spectrum analysis. The
wavelet covariance is shown to decompose the covariance between two
stationary processes on a scale by scale basis. Asymptotic normality
of estimators of the wavelet covariance and correlation is shown in
order to construct approximate confidence intervals. Both quantities
are generalized into the wavelet cross-covariance and
cross-correlation in order to investigate possible lead/lag relations
in bivariate time series.20
Atmospheric measurements (such as station pressure and zonal wind
speeds) from a single station at Canton Island (2.8B0S, 171.7B0W) are
analyzed and nicely replicate the results found in Madden and Julian
(1971). To highlight that the wavelet methods can provide insight over
and above traditional spectral methods (including multitaper
techniques) a daily "Southern Oscillation Index" and station pressure
series from Truk Island (7.4B0N, 151.8B0W) are analyzed. The wavelet
cross-covariance nicely decomposes the usual cross-covariance into
scales which are more easily associated with physical phenomena. The
time-varying wavelet covariance is used to show the increase in
positive correlation between the SOI and Truk Island station pressure
in the first half of each year versus latter half.20
Brandon Whitcher
EURANDOM, P.O. Box 513, 5600 MB Eindhoven, The Netherlands
+31 40 247 8104 (voice) +31 40 247 8190 (fax)
http://www.eurandom.tue.nl/whitcher
------------------------------
Date: Tue, 13 Oct 1998 17:11:46 +0200
From: Lars Lippert <lars.l...@alcatel.ch>
Subject: #12 Dissertation: Wavelet-based volume rendering
DISSERTATION: Wavelet-based volume rendering
Abstract This thesis discusses theoretical and practical improvements
to volume rendering in the context of visual data exploration and
realistic rendering of three-dimensional data sets. Despite the
increasing importance of volume rendering in the field of scientific
visualization, state-of-the-art algorithms still suffer from some
major shortcomings. Difficulties include the numerical complexity as
well as the high memory costs. This work presents a solution to these
key problems by introducing synergy-effects, provided by the
combination of the wavelet theory and new volume rendering
approaches. On basis of this combination, three concepts are presented
for the computation of global and local illumination scenarios.
First, a new physically-based volume radiosity model is derived from
the underlying transport theory model, which counts for both direct
illumination and indirect illumination due to multiple
interreflections of light. The global cube concept focuses on
hierarchical approximations of the energy transfer within a pure
volumetric environment. This concept is designed to meet the
requirements of an accurate and fast computation scheme by using
modern graphics hardware and efficient data topologies.
Next, by neglecting indirect illumination effects, a new concept of
wavelet-based image order volume rendering is derived. This technique
extends classical rendering strategies, as it allows the formulation
of a hierarchical rendering concept for locally illuminated data sets.
Further-more, global and local filtering operations of the wavelet
transformed data sets are proposed to further compress the data and to
increase the rendering speed. The analytic representation of the used
B-spline wavelets provides realistic shading effects and analytic
error bounds.
Finally, by further assuming an isotropically absorbing medium, a new
object order volume rendering approach is presented, which unifies
efficient projection methods and the hierarchical representation of
the data set in the wavelet space. This progressive rendering concept
is performed by superimposing 2D textures and provides interactive
volume visualization. The linearity of the rendering scheme allows the
implementation of a highly efficient data coding strategy that
encompasses the advantages of the wavelet transform and effective
color space transformations.
For each of these concepts, extensive error and performance analyses
of the implemented prototypes are discussed. The analyses clearly
prove the superiority of the introduced concepts.
It can be downloaded from:
ftp://ftp.inf.ethz.ch/pub/publications/dissertations/th12612.pdf
Lars Lippert
Alcatel Switzerland
Telecom Software and Services
------------------------------
Date: Fri, 18 Sep 1998 14:15:46 -600
From: "George Anastassiou" <anas...@msci.memphis.edu>
Subject: #13 Web: JoCAAA Web page
The new JOURNAL OF COMPUTATIONAL ANALYSIS AND APPLICATIONS now has
a web page:
http://www.msci.memphis.edu/~anastasg/anlyjour.htm
Please visit our homepage!
JoCAAA is calling for papers and subscriptions(PLENUM).
First issue due to 1-1-99.
Sincerely Yours
George Anastassiou
Editor in-Chief JoCAAA
University of Memphis
Memphis,TN,USA.
------------------------------
Date: Thu, 24 Sep 1998 11:42:10 -0400 (EDT)
From: Gil Strang <g...@math.mit.edu>
Subject: #14 Meeting: Wavelet Workshop Dec 16-18 in Houston
FIRST ANNOUNCEMENT
WORKSHOP COURSE ON WAVELETS AND FILTER BANKS
taught by Gilbert Strang (MIT) and Truong Nguyen (Boston University)
Wednesday-Thursday-Friday **December 16-17-18, 1998**
at the University of Houston
TEXT: Participants will receive the new textbook (revised edition in 1997)
WAVELETS AND FILTER BANKS by Strang and Nguyen
Wellesley-Cambridge Press, Box 812060, Wellesley MA 02482
This text is already in class use in many EE and mathematics departments.
It can be ordered directly by email: g...@math.mit.edu
We also have a new IMAGE CODER by Truong Nguyen (1997)
This will be used at the Workshop and will be provided to participants.
The Workshop covers four broad topics:
1. Analysis of Filter Banks and Wavelets
2. Design Methods
**3. Applications (from Lecturers and Participants)
*** This workshop will have a specific discussion of
Wavelets in Geophysics
4. Hands-on Experience with Software (including image coding)
These four key areas will be developed in detail:
1. Analysis
Multirate Signal Processing: Filtering, Decimation, Polyphase
Perfect Reconstruction and Aliasing Removal
Matrix Analysis: Toeplitz Matrices and Fast Algorithms
Wavelet Transform: Pyramid and Cascade Algorithms
Daubechies Wavelets, Orthogonal and Biorthogonal Wavelets
Smoothness, Approximation, Boundary Filters and Wavelets
Time-Frequency and Time-Scale Analysis
2. Design Methods
Spectral Factorization
Cosine-Modulated Filter Banks
Eigenfilters and Quadratic Constrained Least Squares
Lattice Structure
The Lifting Method (Ladder Structure)
3. Applications
Audio and Image Compression, Quantization Effects
Transient Detection and Edge Detection
Digital Communication and Multicarrier Modulation
Transmultiplexers
Medical Imaging and Scientific Visualization
Image Compression / Image Segmentation / Image Enhancement
Video Compression
** Deblocking algorithm for JPEG (DCT) Compression
** Deringing algorithm for wavelet-based compression
** Wavelets vs. Fourier Methods in Geophysics
4. Simulation Software
MATLAB Wavelet Toolbox
ECG Compression
New IMAGE CODER
The goal of the Workshop is to be as useful as possible to all
participants. ***** Please request information by an email message*****
with subject Workshop to the organizer Gilbert Strang: g...@math.mit.edu
We will reply about the program and tuition cost and housing.
The tuition includes the textbook and software. It will be the same as
in 1995, 1996, 1997, and June 1998 (San Jose, Tampa, San Diego, Fairfax
and Wellesley Workshops). Tuition is reduced by 50% for graduate students.
We are very glad to answer all questions by email. Our Web sites are
Gilbert Strang Room 2-240 MIT Cambridge MA 02139
617 253 4383 fax 617 253 4358 g...@math.mit.edu www-math.mit.edu/~gs
------------------------------
Date: Fri, 9 Oct 1998 20:07:11 +0800 (SST)
From: Tang Wai Shing <mat...@math.nus.edu.sg>
Subject: #15 Meeting: Workshop on Wavelets in Biomedicine
Workshop on Wavelets in
Biomedical Applications and Information Processing
Date: 21-22 December 1998
Venue: Science Auditorium (LT31), Block S16,
Faculty of Science,
National University of Singapore
Singapore
Organiser: Wavelets Strategic Research Programme,
Department of Mathematics,
National University of Singapore,
Singapore
Objective: The objective of this two-day workshop is to bring together
researchers in Computer Science, Computational Science, Engineering,
Mathematics and Science from the academia and the industry to discuss
recent developments, to identity problems, and to embark on
multidisciplinary research in the applications of wavelets to signal
processing, biomedical imaging and information processing.
Preliminary Programme:
21 December 1998
Section A
A. Aldroubi, Vanderbilt University, USA
Sampling, wavelets, and applications to signal
and image processing, Part I
A. Aldroubi, Vanderbilt University, USA
Sampling, wavelets, and applications to signal
and image processing, Part II
Section B
W. Lawton, National University of Singapore
Homogenization and biophysics
M. Yamada, University of Tokyo, Japan
Wavelets from a view point of application to data analysis
M. Yamada, University of Tokyo, Japan
Some applications of wavelets to time-frequency analysis
of scientific data
22 December 1998
Section C
A. Aldroubi, Vanderbilt University, USA
Wavelets in biology and medicine, Part I
A. Aldroubi, Vanderbilt University, USA
Wavelets in biology and medicine, Part II
Section D
E. C. Chang, National University of Singapore
Foveation and its applications in image compression
R. Viswanathan, CIEMED, National University of Singapore
Applications of multiresolution methods in biomedicine, Part I
R. Viswanathan, CIEMED, National University of Singapore
Applications of multiresolution methods in biomedicine, Part II
Wavelets Strategic Research Programme, National University of Singapore
Software Demonstration
Registration:
If you and/or your colleagues wish to attend the Workshop,
please send an e-mail, before 30 November 1998, to
work...@wavelets.math.nus.edu.sg
stating the names of the participants, their institutions, postal
addresses and e-mail addresses. There is no registration charge.
The final programme will be sent to those who have registered.
For relevant information and latest update, please visit the web-site
http://wavelets.math.nus.edu.sg
Acknowledgement: Funded by the National Science and Technology Board
and the Ministry of Education, Republic of Singapore.
W. S. Tang
Department of Mathematics
National University of Singapore
10 Kent Ridge Crescent
Singapore 119260
E-mail: mat...@math.nus.edu.sg
------------------------------
Date: Thu, 8 Oct 1998 13:26:20 +0300
From: petu...@pdmi.ras.ru
Subject: #16 Meeting: Mathtools 99, St-Petersburg
MATHTOOLS'99
2nd International Conference
"Tools for Mathematical Modelling"
Saint-Petersburg State Technical University,
Saint-Petersburg, Russia
1999, June 14-19
FIRST ANNOUNCEMENT AND CALL FOR PAPERS
MATHTOOLS'99 is a multidisciplinary conference on latest advances in
the theory of ordinary differential equations and the role of the
theory for explanation of some nonlinear effects arising in real
systems as well as demonstration of up-to-date efficient methods for
solving of applied technical problems, providing an ideal forum for
researchers to disseminate knowledge, research results and
applications in many sectors of activity. This will be the second of
a series of conferences initiated in 1996, and organized by the State
Technical University of Saint-Petersburg. Conference sessions will be
started by a 1-hour invited lecture followed by contributed papers, 20
minutes each. Invited talks will highlight some of the major
accomplishments, trends and problems in the theory.
Working languages
The working languages are English and Russian.
Topics of interest
Papers may address a broad range of research fields of current
interest. A list of possible topics includes (but is not limited to)
the following:
* Mathematical modelling
* Computer algebra
* Design techniques
* Numerical methods
* Parallel and distributed algorithms
* Computer modeling in dynamical systems
* Mathematical models in biology, medicine, ecology etc.
* Applications to physics, electrotechniques, and electronics
* Dynamic economic models
* General macro-economic models
* Market models
* Wavelets and their applications
Organizing committee
Chairman - G.S.Osipenko (St.Petersburg Technical University)
Secretary - Yuri Ivanov (St.Petersburg Technical University)
Scientific committee
Leonid Belous (Ukraine)
Daniel Dytte (Denmark)
Jens Hugger (Denmark)
Alexander Kasterin (Russia)
Vasiliy Malozemov (Russia)
Marian Mrozek (Poland)
Alexander Petukhov (Russia)
Mika Seppala (USA)
Vasily Strela (USA)
Gillian Tardivel (UK)
Valeriy Tkachenko (Ukraine)
Vyacheslav Zavadskii (Belorussia)
Valery Zheludev (Israel)
Alexei Zhizchenko (Russia)
Sergei Znamensii (Russia)
Dates to remember
* Abstracts due: April 30, 1999
* Registration form: April 30, 1999
* Meeting in St. Petersburg: June 14-19, 1999
Abstracts
The papers selection for the meeting will be made on the basis of an
abstract.
The abstract (in 1-2 complete pages, hard copy only)
should include the title of the paper, names of all
authors, addresses and complete
affiliations, and appropriate references.
The abstracts and the Registration forms
for the section "Wavelets and their applications"
can be sent to Alexander Petukhov by e-mail:
petu...@pdmi.ras.ru
Meeting site
Saint-Petersburg State Technical University,
Polytechnicheskaya st. 29, St. Petersburg
Meeting secretariat
Yuri Ivanov
MATHTOOLS'99
Dept. of Mathematics
State Technical University
Polytechnicheskaya st., 29
St.Petersburg 195251, Russia
Fax.: +7+812+5343314
+7+812+5341404
e-mail: l...@osipenko.stu.neva.ru
ma...@math.hop.stu.neva.ru
petu...@pdmi.ras.ru
------------------------------
Date: Thu, 15 Oct 1998 17:22:43 +0200
From: Evelyne Lutton <evelyne...@inria.fr>
Subject: #17 Meeting: Fractals in Engineering, Delft
CALL FOR PAPERS
L'INGENIEUR ET LES FRACTALES
FRACTALS IN ENGINEERING
June 14-16 1999, Delft, The Netherlands
Objectives
----------
The goal of the conference is to bring together researchers working in
all areas of fractal analysis. The scope encompasses recent
theoretical advances as well as industrial applications. The first
symposia (June 3-5, 1992, and June 1-4, 1994, in Montreal, June 25-27,
1997 in Arcachon, France) were most successful in stimulating
relations between the academic and private sectors. We hope to renew
this experience with the fourth issue held in the Netherlands.
Scope
-----
Topics to be covered include, but are not limited to :
THEORETICAL ASPECTS :
- Dimension theory
- Multifractal Analysis
- IFS theory
- Harmonic Analysis on Fractals
- Dynamical systems
- Wavelet and Fractals
- Stochastic Analysis on Fractals
APPLICATIONS :
- Signal Processing
- Image Processing
- Finance
- Fractal-Wave Interactions
- Computer Networks Traffic Analysis
- Processes on Fractal Surfaces
- Mechanical Aspect of Fractals
Structure
---------
Two thematic sessions are scheduled per day. Each will be introduced
by an invited lecture with a didactic approach allowing a formal
introduction for non-specialists.
Several 25-minutes periods of contributed talks will follow.
Poster sessions will be organized.
Scientific Committee
--------------------
Michel DEKKING (Delft University of Technology, The Netherlands),
Jacques LEVY VEHEL (INRIA Rocquencourt, France),
Evelyne LUTTON (INRIA Rocquencourt, France),
Claude TRICOT (Universite de Clermont-Fd, France).
Honorary Chairman
-----------------
Benoit B. MANDELBROT (Yale University, USA),
Program committee (preliminary)
-------------------------------
Mitzi ADAMS (NASA/Marshall Space Flight Center, USA),
Pierre ADLER (IPGP, Paris, France),
Albert BENASSI (Universite de Clermont-Fd, France),
Serge COHEN (Universite Versailles-St-Quentin en Y., France),
Marc-Olivier COPPENS (Delft University of Technology, The Netherlands),
Michel GERSPACHER (SID Richardson Carbon Co., USA),
Michel GUGLIELMI (IrCyn, Ecole Centrale Nantes, France),
Stephane JAFFARD (Ecole Normale Superieure, France),
Dwight L. JAGGARD (University of Pennsylvania, USA),
James MARTIN (Sandia Lab, USA),
Ilkka NORROS (VTT Telecommunications, Finland),
Dietmar SAUPE (Universit"at Leipzig, Germany),
Zbigniew R. STRUZIK (CWI, The Netherlands),
Eric TOSAN (Universite Lyon I, France),
Edward VRSCAY (University of Waterloo),
Christian WALTER (Coopers & Lybrand, France).
Invited speakers (preliminary)
-----------------------------
Kenneth J. FALCONER (University of St. Andrews, Scotland),
Patrick FLANDRIN (ENS Lyon, France),
Massimiliano GIONA (Universita di Cagliari,Italy),
Bernard SAPOVAL (Ecole Polytechnique, Palaiseau, France).
Local Organization :
--------------------
Annick THEIS-VIEMONT (INRIA Rocquencourt, France),
Marie-Claude SANCE (INRIA Rocquencourt, France).
Conference Secretariat
------------------
INRIA Rocquencourt,
Relations Exterieures, Bureau des cours et colloques
B.P. 105 78153 LE CHESNAY Cedex, France
Tel : +33 1 39 63 56 00
Fax : +33 1 39 63 56 38
Email : FE...@inria.fr
Call for communications
-----------------------
Anyone involved with fractal analysis and/or applications in
engineering or applied sciences, and interested in giving a talk or
presenting a poster is welcome to submit 4 copies of a full paper
(maximum 15 A4 pages) to the conference secretariat.
Electronic submissions are welcome (e-mail : FE...@inria.fr).
Proceedings
-----------
All selected papers (oral and poster presentation) will be included in
the FE99 conference proceedings, a selection of papers will be
considered (additional review process) for publication in a Springer
Verlag book.
Calendar
--------
Deadline for reception of papers : November 30th, 1998
Notification of acceptance : January 31th, 1999
Deadline for reception of final papers : March 15th, 1999
PRACTICAL INFORMATION
----------------------
A Web site is available providing the most recent
information about the conference :
http://www-rocq.inria.fr/fractales/FE99.html
------------------------------
Date: Fri, 16 Oct 1998 11:02:33 +0100
From: Michael Unser <michae...@epfl.ch>
Subject: #18 Meeting: SPIE Wavelet Applications VII
Call for Papers and Announcement
Wavelet Applications in Signal and Image Processing VII (SD84)
Part of SPIE's International Symposium on
Optical Science, Engineering, and Instrumentation
18-23 July 1999 * Colorado Convention Center * Denver, Colorado USA
Conference Chairs: Michael A. Unser, Swiss Federal Institute of Technology
(Switzerland); Akram Aldroubi, Vanderbilt Univ.; Andrew F. Laine, Columbia
Univ.
Program Committee: Jean-Pierre Antoine, Univ. Catholique de Louvain
(Belgium); Richard G. Baraniuk, Rice Univ.; John J. Benedetto,
Univ. of Maryland/College Park; Douglas P. Hardin, Vanderbilt Univ.;
Dennis M. Healy, Jr., DARPA/Dartmouth College; Bjorn D. Jawerth,
Univ. of South Carolina; Kurt Jetter, Univ. Hohenheim (Germany);
Jelena Kovacevic, Lucent Technologies/Bell Labs.; Arun Kumar,
Southwestern Bell Technology Resources Inc.; Jean-Marc Lina, Univ. de
Montreal (Canada); Francois G. Meyer, Yale Univ.; Truong Q. Nguyen,
Boston Univ.; Thomas Strohmer, Univ. of California/Davis; P. P.
Vaidyanathan, California Institute of Technology
Keynote Speaker: Wim Sweldens, Lucent Technologies/Bell Labs.
The analysis of signals and images at multiple scales is an attractive
framework for many problems in computer vision and signal and image
processing. Wavelet theory provides a mathematically precise
understanding of the concept of multiresolution. This conference,
which is open to researchers in mathematics, signal and image
processing, computer vision, medical imaging, and physics, will focus
on novel applications of wavelet-based signal analysis and processing
methods, refinements of existing techniques, and new theoretical
developments. One of the primary goals will be to facilitate
interdisciplinary exchange and to generate cross-fertilization between
these various fields of research.
Topics for the conference may include but are not limited to:
* wavelet compression, coding
* wavelet theory and multirate filterbanks
* frames and over-complete representations
* multiresolution algorithms
* Gabor transforms and space-frequency localization
* wavelet-based noise reduction and restoration
* wavelet-based feature extraction and detection
* wavelet texture analysis and segmentation
* wavelet-based fractal analysis
* multiscale random processes
* wavelets and approximation theory
* image representations from wavelet maxima or zero-crossings
* wavelets in medical imaging.
Note: Please follow the submission instructions. In addition, please submit
an extended abstract of 2 pages plus as many figures as needed (instead of
the 250 words), and replace the brief biography by a summary cover sheet
that includes:
1. Description of the problem addressed: why is it important?
2. What is the original contribution of this work: how does it compare
with other authors? Do NOT submit abstracts with figures by email,
use FAX or regular MAIL only.
Abstract Due Date: 21 December 1998
Manuscript Due Date: 21 June 1999
For more information on the Annual Meeting or a complete listing of all
conferences please go to our SPIE Web site:
www.spie.org/info/annualmeeting.html
Michael Unser, Professor
Biomedical Imaging Group
Swiss Federal Institute of Technology
EPFL, DMT/IOA, BM
P.O. Box 127
CH-1015 Lausanne
Switzerland
E-Mail: michae...@epfl.ch
URL : http://bigwww.epfl.ch/
Tel.: +41(21)693.51.75
Secr.: +41(21)693.51.85
=46ax : +41(21)693.37.01
------------------------------
Date: Wed, 30 Sep 1998 21:39:01 EDT
From: ati...@aol.com
Subject: #19 Course: Mathematical & Physical Wavelets
COURSE ANNOUNCEMENT:
Mathematical & Physical Wavelets: November 16-19 1998 and March 8-11,1999
=95November 16-19, 1998
at the Quality Hotel Courthouse Plaza, 1200 N. Courthouse Rd,
Arlington, VA 22101, Phone (703) 524-4000.
=95March 8-11, 1999 at the Days Inn, 1234 Soldiers Field Rd,
Boston, MA 02135, Phone (617) 254-1234.
http://catalog.com/hitekweb/sked.htm
SUMMARY:
Wavelet analysis has undergone an explosive growth in the past few
years, = with many successes in the efficient analysis, processing,
and compression of signals and images. It is based on the idea of
time-scale decomposition of signals and images, which is fundamentally
different from the traditional frequency and time-frequency
decompositions. Unfortunately, many potential users of this new
technique are hindered by the inaccessibility of its mathematical
framework, partly due to its novelty. The objectives of this course
are as follows:
a) To give a practical introduction to space-time-scale analysis in
one an= d two dimensions, and show that it may be regarded as a
wideband generalizat= ion of the usual time-frequency analysis.
b) To develop space-time-scale analyses specifically dedicated to
acoustic and electromagnetic waves, and apply them to sonar and
radar.
Each participant will receive a copy of Dr. Kaiser's textbook "A
Friendly Guide to Wavelets," as well as a newly updated 235-page
packet of typeset lecture notes with many graphical examples. For a
description and reviews of the textbook, please visit the author's
website at www.wavelets.com.
INSTRUCTOR:
Dr. Gerald Kaiser heads the Virginia Center for Signals and Waves. He
has = a Ph.D. in physics from the University of Wisconsin-Madison, and
a Ph.D. in mathematics from the University of Toronto. His research
has concentrated= on developing a theory of acoustic and
electromagnetic wavelets with applications to sonar and radar. He has
published many papers on mathemati= cs, physics and signal processing,
as well as two books: Quantum Physics, Relativity, and Complex
Spacetime and A Friendly Guide to Wavelets, (Birkhauser, 1994).
REGISTRATION AND INFORMATION:
For registration or more information call (410) 531-6034, email
"ati...@aol.com" or visit the ATI homepage http://catalog.com/hitekweb
------------------------------
Date: Mon, 5 Oct 1998 19:00:24 -0400 (EDT)
From: Ivan Selesnick <sel...@taco.poly.edu>
Subject: #20 Job: PhD Fellowships at Polytechnic University - Brooklyn
I'd like to let students interested in doing wavelet-related
research know that several fellowships are available at Poly
for Jan 99.
- Ivan Selesnick
sel...@taco.poly.edu
Announcement for Research Fellowships
Electrical Engineering Department
Polytechnic University
Six Metrotech Center
Brooklyn, New York 11201
U.S.A.
Several research fellowships are available beginning Spring '99 for
students who are interested in pursuing their Ph.D. in the Electrical
Engineering Department. These research scholarships are very
competitive and highly qualified candidates are encouraged to apply
for these positions. It is required that applicants have a high grade
point average and strong GRE scores. The Electrical Engineering
Department enjoys a strong national reputation and is ranked 12th in
its undergraduate program and 24th in its graduate program. The
department engages in over 2.5 million dollars of external research
annually in the following areas: Telecommunications, signal
processing, control, wireless, communication, robotics, computer
engineering, electromagnetics, and power.
Interested applicants should send their applications to the Electrical
Engineering Department with a cover letter stating their
qualifications for the research fellowships. Applications will also be
posted on the departmental web pages and may be reached through the
university web pages at http://www.poly.edu.
------------------------------
Date: Thu, 8 Oct 1998 15:37:00 +0100 (BST)
From: Guy Nason <g.p....@bristol.ac.uk>
Subject: #21 Job: Research Associate, University of Bristol
UNIVERSITY OF BRISTOL
Department of Mathematics
Research Associate in Statistics
Applications are invited for a Research Associate (Grade RA1A)
position in Statistics, tenable from a date to be agreed, as soon as
possible for the following project funded by a grant from the EPSRC
jointly awarded to Guy Nason and Bernard Silverman:
Novel wavelet methods in statistics
Further details are available electronically via
http://www.stats.bris.ac.uk/~guy/Research/Jobs/job.html
University of Bristol Department of Mathematics
Postdoctoral Research Associate Position
Novel wavelet methods in Statistics
An EPSRC-funded research associate position is available for work on
novel wavelet methods in statistics for a period of up to 2 years with
Dr Guy Nason and Professor Bernard Silverman, FRS.
Applicants should have, or expect soon to have, a PhD in Mathematics
or Statistics. Some prior knowledge of wavelet theory and/or the
statistical package SPlus would be useful but is not a prerequisite.
A knowledge of the C programming language would also be attractive but
certainly not necessary.
For further details telephone +44 (0) 117 925 6450, minicom +44 (0)117
928 8894 or E-mail Recru...@bris.ac.uk (stating postal address
ONLY) quoting reference number 5104)
The closing date is 6th November 1998.
Salary on the RA1A scale (15,735 to 23,651 pounds per year).
For further informal details please contact:
* Dr G Nason, Department of Mathematics, University of Bristol,
University Walk, Bristol, England, BS8 1TW.
Telephone: +44 (0) 117 928 8633.
Fax: +44 (0) 117 928 7999.
Email: G.P....@bristol.ac.uk
or
* Professor B W Silverman, FRS, Department of Mathematics,
University of Bristol, University Walk, Bristol, England, BS8 1TW.
Telephone: +44 (0) 117 928 7968.
Fax: +44 (0) 117 928 7999.
Email: B.W.Si...@bristol.ac.uk
The University of Bristol is AN EQUAL OPPORTUNITIES EMPLOYER.
------------------------------
Date: Mon, 12 Oct 1998 00:49:30 +0200
From: Baltzer Science <mai...@ns.baltzer.nl>
Subject: #22 Contents: Numerical Algorithms 18-1
Numerical Algorithms 18 (1998) 1
Herbert H.H. Homeier
An asymptotically hierarchy-consistent, iterative sequence transformation
for convergence acceleration of Fourier series 1-30
Gorik De Samblanx and Adhemar Bultheel
Nested Lanczos: implicitly restarting an unsymmetric Lanczos algorithm
31-50
Z. Bartoszewski and Z. Jackiewicz
Construction of two-step Runge--Kutta methods of high order for ordinary
differential equations 51-70
M.O. Bristeau and J. Erhel
Augmented conjugate gradient. Application in an iterative process for the
solution of scattering problems 71-90
Birkett Huber and Jan Verschelde
Polyhedral end games for polynomial continuation 91-108
Book reviews 109-112
------------------------------
Date: Sat, 19 Sep 1998 20:59:06 +0100 (WET DST)
From: "F.D. Murtagh" <fmur...@cdsxb6.u-strasbg.fr>
Subject: #23 Answer: Wavelets in fault diagnsosis (WD 7.9 #19)
> I am a Marine engineer turned Computer science reseracher! The area
> of my research is "Developing early warning systems for machinery".
> I have collected vast amounts of data from a 2 cylinder, 4-stroke
> Diesel engine.
> of data. I am planning to compress the data using wavelets and then
> use the highest 3 or 4 coefficients from each level as inputs to a
For noise modeling, see Starck, Murtagh and Bijaoui, Image and Data
Analysis: the Multiscale Approach, Cambridge Univ Press, 1998. (Uses
variance stabilization for various noise models. Subsequent work
handles stationary and non-stationary, multiplicative and additive,
heteroscedastic etc. cases).
For feature definition in an application not unlike process control,
see Aussem, Campbell and Murtagh, "Wavelet-based feature extraction
and decompostion strategies for financial forecasting", Jnl.
Computational Intelligence in Finance, 6, 5-12, 1998. (Uses
shift-invariant a trous to (i) decompose, carry out forecasts, and
combine, and (ii) define a feature vector for each time-value using
wavelet transform.)
Regards,
Fionn Murtagh
Prof F Murtagh, Fac Informatics, Univ Ulster, BT48 7JL Nth Ireland
http://www.infm.ulst.ac.uk/~fionn fd.mu...@ulst.ac.uk
------------------------------
Date: Mon, 21 Sep 1998 11:30:58 +0100
From: Mr P E Davies <p.e.d...@ic.ac.uk>
Subject: #24 Question: Seismic data compression
Hi,
I am a PhD student in the geology department of Imperial College,
London. I am looking for some refernces on the use of wavelets in the
compression of seismic data. I hope someone can point me in the right
direction,
Thanks,
Paul Davies
------------------------------
Date: Thu, 24 Sep 1998 13:31:21 +1000
From: Richard Andrews <and...@postoffice.utas.edu.au>
Subject: #25 Question: Calling all Quincunx wavelet filters
Hi, I'm working on my PhD thesis in wavelet image compression and I'm
looking for
(a) information on how to construct wavelet filters in two dimensions for use
on the Quincunx lattice. I come from an engineering rather than mathematical
background so what I really want is a HOW TO guide rather than a mathematical
dissertation.
(b) any filters suitable for the Quincunx lattice that anyone may have
developed. I'm looking for all types of filters: orthog, biorthog, linear
phase, etc etc etc. The more the better and any size is useful to me.
(c) info on the psychovisual response of the human visual system to wavelet
bases in two dimesnions(as opposed to straight spatial frequency).
Thank you very much for any assistance
Rich
Richard Andrews
Graduate Research Student
Electrical Engineering and Computer Science
University of Tasmania
BOX 252-65, Hobart, Australia
email : <Richard...@utas.edu.au>
phone (w) : +61 3 6226 2137
web : http://www.eecs.utas.edu.au/cgi/postgrad/andrews
------------------------------
Date: Fri, 25 Sep 1998 11:20:07 +0800
From: Paul Abbott <pa...@physics.uwa.edu.au>
Subject: #26 Question: Orthogonalizing a non-orthogonal family of wavelets?
If a set of basis functions, {f[t-k]}, are not orthonormal we can
orthogonalize them in Fourier space by dividing (using pseudo-Mathematica
notation)
fhat[w] = FourierTransform[f[t],w],
by the square root of
Sum[Abs[fhat[w + 2 Pi l]]^2, {l, -Infinity, Infinity}],
and then computing the inverse FourierTransform. E.g., using this method it
is relatively easy to orthogonalize the B-spline functions. However, it
seems to me that the computation of the inverse FourierTransform is, in
general, be non-trivial.
[1] Are there any papers or references on using the DFT/FFT on sampled
values of a non-orthogonal family of wavelets to perform the
orthogonalization? Is this a practical approach?
[2] A simple-minded direct approach is to form the linear combination
phi[t] = Sum[a[k] f[t+k],{k,-kmax, kmax}],
(truncating the, in general, infinite sum), compute the overlap integrals,
<k> = Integrate[f[t] f[t+k], {t,-Infinity,Infinity}] = <-k>,
require orthonormality,
Integrate[phi[t] phi[t+k], {t,-Infinity,Infinity}] = KroneckerDelta[k,0]
and then use least-squares to determine the "best" values of a[k] for a
particular kmax. I assume that this idea must have appeared in the
literature somewhere. Does anyone have pointers to relevant literature?
Is this a practical or useful approach?
Paul Abbott Phone: +61-8-9380-2734
Department of Physics Fax: +61-8-9380-1014
The University of Western Australia
Nedlands WA 6907 mailto:pa...@physics.uwa.edu.au
AUSTRALIA http://www.physics.uwa.edu.au/~paul
------------------------------
Date: Thu, 01 Oct 1998 12:26:28 +0200
From: Per Bodin <per....@s3.kth.se>
Subject: #27 Question: Wavelet compression of satellite attitude
Hi,
Does anybody know if wavelets have been used for compact
representations of attitude references for satellites? Are there any
other suitable bases? The idea is to provide compact on-board storage
of where the satellite shall point while keeping the interpolation
error small. I know that Chebychev polynomials are used for
representations of positions in orbits but representation of attitude
is a somewhat different issue. I would be grateful if someone could
give me a reference on this.
Regards,
/Per Bodin
Per Bodin, PhD tel:+46-8-790-74-24
S3-Automatic Control fax:+46-8-790-73-29
Royal Institute of Technology mailto:b...@s3.kth.se
S-100 44 STOCKHOLM, SWEDEN http://www.s3.kth.se/~bod
------------------------------
Date: Tue, 06 Oct 1998 15:59:16 +0100
From: =?iso-8859-1?q?ciar=e1n_o=27leary_=3ccolear.ca4=40compapp.dcu.ie=3e?=@compapp.dcu.ie
Subject: #28 Question: Wavelets' role in Pattern recognition
Readers,
As part of a final year project I am attempting to investigate how
wavelets can be used in the field of pattern recognition, and how
their performance compares to that of more classical methods such as
neural nets and fuzzy logic. I am relatively new to this field so if
anyone could supply me with any advice or sources of
information(web-sites, books, papers, publications, etc.) would be
most grateful.
My e-mail address is colea...@compapp.dcu.ie
Rgds,
Ciar=E1n O'Leary
Dublin City University
------------------------------
Date: Sat, 10 Oct 1998 16:12:13 +1000
From: Dennis Lee <denni...@eng.monash.edu.au>
Subject: #29 Question: Few problems using wavelet network for vibration transients
Dear experts
I use wavelet packet and backpropagation neural network to analyse the
vibration transients now. The traditional constructions of neural
networks by random initization and traning procedure have a lot of
drawbacks. My question is how to improve the determination of the
network size and estimation of the network parameters systematically?
Thanks in advance for any suggestion.
email: denni...@eng.monash.edu.au
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End of Wavelet Digest 7 Issue 10
************************************
Reposted by
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(Phone: 416-978-7075) k...@cs.utoronto.ca
(FAX: 416-978-1931) http://www.cs.utoronto.ca/~krj
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