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Distributed
Signal Processing for Sensor Networks
Martin Vetterli
Ecole Polytechnique Federale de Lausanne (EPFL) and UC Berkeley
Abstract:
A sensor network is a spatio-temporal
sampling device with a wireless communications infrastructure. In this
talk, after a short overview of the
Center on Mobile Information and Communication Systems, we will
address the following questions:
1. The spatio-temporal structure of distributed signals, with an
emphasis on the physics behind the signals, and results on sampling.
2. The interaction of distributed source compression and transmission,
with a particular focus on joint source-channel coding.
3. Applications in environmental monitoring, like for example
tomographic measurements, and a description of a large scale
environmental
monitoring project in the Swiss Alps.
This is joint work with T.Ajdler, G.Barrenetxea, H.Dubois-Ferriere,
I.Jovanovic, R.Konsbruck, L.Sbaiz (EPFL), R.Cristescu (Caltech),
P.L.Dragotti (Imperial) and M.Gastpar (UC Berkeley).
The work is sponsored by the
Center on Mobile Information and Communication Systems, funded by
the Swiss National Science Foundation.
Biography
Martin Vetterli received his
Engineering degree from ETH in Zurich, his MS from Stanford and his
Ph.D. from EPFL in Lausanne.
In 1986, he joined Columbia University in New York, first with the
Center for Telecommunications Research and then with the Department of
Electrical Engineering where he was an Associate Professor of
Electrical Engineering. In 1993, he joined the University of
California at Berkeley, were he was Full Professor until 1997. Since
1995, he is a Professor at EPFL, where he headed the Communication
Systems Division (1996/1997) and heads the Audiovisual Communications
Laboratory. From 2001 to 2004 he directed the National Competence
Center in Research on mobile information and communication systems.
Since October 2004, he is Vice-President for International Affairs at
EPFL. He has held visiting positions at ETHZ (1990) and Stanford
(1998).
His research interests are in the areas of applied mathematics, signal
processing and communications. He is the co-author of a textbook on
“Wavelets and Subband Coding”, and of over 100 journal papers.
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V.
John Mathews Department
of Electrical & Computer Engineering
University of Utah
Salt Lake City, UT 84112
Email:
mathews@ece.utah.edu
Wednesady Sept. 06, 2006 - Auditorium
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Signal
Processing in Maternal-Fetal Medicine
V. John Mathews
University of Utah
Abstract
Between 3 and 8% of pregnant women
develop preeclampsia. Approximately one third of these women have
serious complications including fetal or perinatal death, premature
and small-for-gestational age infants, maternal cerebrovascular
accidents, congestive heart failure, and maternal death. Preeclampsia
represents an annual health care expense in excess of $5 billion per
year in medical care for mothers and premature infants in the United
States alone. In addition, many scientists believe that the burden of
cardiovascular disease in adults begins in the developmental process
and may have roots in maternal-fetal diseases like preeclampsia and
intrauterine growth restriction. In spite of dramatic reductions in
maternal, fetal and newborn morbidity and mortality, the occurrence
rate of preeclampsia has remained unchanged during the last century.
This talk will review current research work on early detection of
preeclampsia and other maternal fetal diseases that has origins in
abnormal placental development. We will start with an overview of the
physiological changes that take place in the mother and fetus during
pregnancy. We will discuss how the maternal and fetal circulations
systems are affected by pregnancy-related diseases, and explore some
of the biochemical changes associated with maternal-fetal diseases. We
will then go on to show how signal processing techniques can be
applied to detect and characterize many differences between normal and
abnormal pregnancies. In general, no one aspect or measurement is able
to predict the diseases with high sensitivity and specificity.
Multivariate approaches for prediction of maternal-fetal diseases will
be discussed. Such techniques will allow physicians to assess the
likelihood of the development of preeclampsia and other diseases with
roots in abnormal placental development early during pregnancy, much
before the symptoms of the disease becomes apparent and allowing them
to provide the higher level of care needed by the affected patients.
Biography
Dr. V. John Mathews is a Professor of
Electrical and Computer Engineering at the University of Utah. He
received his Ph. D. and M.S. degrees in Electrical and Computer
Engineering from the University of Iowa , Iowa City, Iowa in 1984 and
1981, respectively, and the B. E. (Hons.) degree in Electronics and
Communication Engineering from the University of Madras, India in
1980. At the University of Iowa, he was a Teaching/Research Fellow
from 1980 to 1984, and a Visiting Assistant Professor in the
Department of Electrical and Computer Engineering during the 1984-85
academic year. He joined the department of Electrical Engineering at
the University of Utah in 1985, where he is engaged in teaching signal
processing classes and conducting research in signal processing
algorithms. He served as the Chairman of the department from 1999 to
2003.
His primary research interests are in adaptive and nonlinear signal
processing and application of signal processing techniques in
communication systems and biomedical engineering. He is the author of
the book Polynomial Signal Processing, published by Wiley, and
co-authored with Professor G. L. Sicuranza, University of Trieste,
Italy. He has published more than one hundred technical papers.
Dr. Mathews is a fellow of IEEE. He has served as a member of the
Signal Processing Theory and Methods Technical Committee, the
Education Committee and the Conference Board and the Publication Board
of the IEEE Signal Processing Society. He was the Vice President (Finance)
of the IEEE Signal Processing Society during 2003-2005. He was elected
to the Board of Governors of the IEEE Signal Processing Society in
2003. He is a past associate editor of the IEEE Transactions on Signal
Processing, and the IEEE Signal Processing Letters. He serves on the
editorial board of the IEEE Signal Processing Magazine at present. He
has served on or is currently serving on the organization committees
of several international technical conferences including as the
General Chairman of the IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP) 2001 and the IEEE DSP Workshop
1998.
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Signal
Processing between research and exploitation
Leonardo
Chiariglione
CEDEO.net
Abstract
In the current dynamic environment the
time between research
and industry adoption is getting shorter and shorter. In its 18 years
of history MPEG has created a new successful paradigm for channeling
research results into exploitation. The talk will look back at what
has
been done and see what must be changed for MPEG to continue serving as
a bridge between academia/research and exploitation.
Biography
Leonardo Chiariglione graduated from
the Polytechnic of Turin and
obtained his Ph. D. degree from the University of Tokyo in 1973.
He has been at the forefront of a number of initiatives that have
helped shape media technology and business as we know them today.
Among these the Moving Pictures Experts Group (MPEG) standards
committee which he founded and chairs and the Digital Media Project of
which he was the proponent and is the current president.
Dr. Chiariglione is the recipient of several awards: among these the
IBC John Tucker Award, the IEEE Masaru Ibuka Consumer Electronics
Award, the Kilby Foundation Award and EURASIP Meritorius Service Award
2002.
Since January 2004 he is the CEO of CEDEO.net, a consulting company
advising major multinational companies on matters related to digital
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H. Vincent
Poor
Michael Henry Strater University Professor Department of Electrical
Engineering Princeton University Princeton, NJ 08544 USA
Email:
poor@princeton.edu
Friday Sept. 08, 2006 - Auditorium room |
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Signal
Processing Across the Layers in Wireless Networks
H. Vincent Poor
Princeton University
Abstract
A major contemporary issue in the
design and deployment of wireless networks is the dramatic increase in
demand for new capacity and higher performance. The development of
these capabilities is limited severely by the scarcity of two of the
principal resources in wireless networks, namely energy and bandwidth.
Consequently, the community has turned to a third principal resource,
the addition of intelligence at all layers of the network, in order to
exploit increases in processing power afforded by Moore's Law type
improvements in microelectronics. This talk will focus on two aspects
of this phenomenon: the impact of advanced physical-layer signal
processing on the higher-layer performance of wireless communication
networks, notably energy efficiency, throughput and delay; and the use
of advanced signal processing principles to improve the efficiency and
efficacy of wireless sensor networks.
Biography
H. Vincent Poor is the Michael Henry
Strater Professor of Electrical Engineering at Princeton University,
where he is involved in research and teaching in statistical signal
processing and its applications in wireless networks and related
fields. Among his publications in these areas is the recent book,
Wireless Networks: Multiuser Detection in Cross-Layer Design. Dr. Poor
is a member of the U.S. National Academy of Engineering and is a
Fellow of the American Academy of Arts & Sciences, the IEEE and other
organizations. During the 2003-04 academic year he was a Guggenheim
Fellow, dividing a sabbatical leave among Imperial College, Stanford
and Harvard. In 2005, he received the IEEE Education Medal.
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