Corrections and changes to the Advanced program will be collected and posted here on 9/16/98, 9/30/98, 10/15/98 and 10/30/98. Corrections need to be received a week before above dates to be available on specified dates.
Please e-mail corrections to snetzorg@nps.navy.mil with copy to asilomar@ece.nps.navy.mil. Thank you.
Corrections as of 9/30/98:
Correct affiliation and address for A. Swami are:
It should be:
Ananthram Swami
Army Research Lab
AMSRL-IS-TA
2800 Powder Mill Road
Adelphi, MD 20783-1197
a.swami@ieee.org
page 7: Brian Sadler and I are listed as co-chairs for
session TP4; the correct chair for the session is
K.K. Parhi
page 7: The chair for session TP8b is Stella Batalama (SUNY-Buffalo)
not J. Li
Session MA7b chair is Glen Landon, U. C. Santa Cruz
Session Mp1a and MP1b, chairs have switched: Ping Wong chairs MP1a
and Lina Karam should chair MP1b
SESSION MP1a, paper 2: new title
Image Browsing using Data Structure based on
multiple Space-filling Curves
Scott Craver, Boon-Lock Yeo and Minerva Yeung
Intel Corporation.
page 22: Session MP2 - Advances in Spectrum Analysis
MP2-6 : wrong affiliation
The affiliation should be
Technische Universitaet Wien
(not Technische Universitaet Witaet Wien)
MP2-7 : missing author, authors in wrong order
The authors (in the correct order) are :
Paulo Goncalves, INRIA;
Rudolf Riedi, and Richard Baraniuk, Rice University
Session MP6 paper 4: new title and abstract:
Panagiotis Tsakalides, Filippo Trinci, and Chrysostomos L. (Max) Nikias
Signal and Image Processing Institute
Department of Electrical Engineering - Systems
University of Southern California
Los Angeles, CA 90089-2564
Phone: (213) 740-6432
FAX: (213) 740-4651
E-mail: tsakalid, nikias@sipi.usc.edu
TITLE:
Radar CFAR Thresholding in Heavy-Tailed Clutter
and Positive Alpha-Stable Measurements
SHORT DESCRIPTION:
This paper shows how to apply Rohling's order-statistics constant false
alarm rate (OS CFAR) algorithm, developed for a Rayleigh background, to
the case of heavy-tailed clutter background. In particular, we study the
performance of the OS CFAR processor when the output measurements of the
square-law detector can be modeled as Positive Alpha-Stable (\pas)
random variables with a shape parameter (characteristic exponent) equal
to 0.5. We derive the exact expressions for the detection and false
alarm probabilities of the OS and cell averaging (CA) CFAR detectors,
and compare their performance by means of their corresponding receiver
operating characteristics.
pages 30-31: Session MP8b
MP8b-5 : affiliation has changed:
S. Gollakota, Southern Illinois University at Carbondate,
and R. Viswanathan, University of Texas at San Antonio
MP8b-6 : wrong author
The first author should be
Shishir Shah
(not Mehmet Oner, ODTU)
MP8b-10 : wrong author
The first author should be
Zhong Zhang
(not Yumin Zhang)
MP8b-11 : spelling error
The second author's name is Tarun Singh
(not Tarun Sing)
MP8b-12 : title changed, and author added:
Numerical Solutions for Optimum Distributed Detection
of Known Signals in Dependent t-Distributed Noise---the
Two Sensor Problem
X. Lin and R. S. Blum, Lehigh University.
MP8b-13 : paper withdrawn
`Distributed detection of a change in distribution'
by Venugopal Veeravalli, Cornell University
has been withdrawn.
Session TA1
TA1-8: first author name correct spelling is: Gollamudi, S.
TA1-5: Modified title and abstract
"A Zero-Forcing Receiver for the DS-CDMA Downlink
Exploiting Orthogonality of Spreading Sequences"
Irfan Ghauri and Dirk T. M. Slock
Abstract:
We address the problem of downlink interference rejection
in a DS-CDMA system. Periodic orthogonal Walsh-Hadamard sequences
spread different users' symbols followed by masking by a symbol
aperiodic base-station specific overlay sequence.
This corresponds to the downlink of the European UMTS wideband
CDMA norm. The point to point propagation channel from the cell-site
to a certain mobile station is the same for all downlink signals
(desired user as well as the interference).
The composite channel is shorter than a symbol
period for some user signals, while other users can have significant
ISI owing to a faster transmission rate. In any case, orthogonality
of the underlying Walsh-Hadamard sequences is destroyed by multipath
propagation, resulting in coherent combination of the desired signal and
multiuser interference if a coherent combiner (the RAKE receiver) is
employed. We propose a linear
zero-forcing (ZF) receiver which equalizes for the estimated
channel, thus rendering the user signals orthogonal again. A simple
code matched filter subsequently suffices to cancel the multiple access
interference (MAI) from intracell users.
Session TA2
Updated title and abstracts for TA2-8
Title: Design of Estimation/Deflation Approaches to Independent
Component Analysis
Authors: Scott C. Douglas, Southern Methodist University, and
S.-Y. Kung, Princeton University
Abstract: Adaptive algorithms for independent component analysis
(ICA) attempt to extract multiple independent source signals from
sets of linear mixtures. In this paper, we consider the design
of one class of algorithms that combine the three tasks of prewhitening,
estimation, and deflation. After reviewing several methods for each of
these tasks, a performance analysis of a general class of
unit-norm-constrained gradient-based extraction methods is derived.
This analysis is then used to determine via calculus of variations
the optimum output nonlinearity for the given algorithm class and
source statistics. These results show that (i) the local convergence
behavior of such algorithms can be significantly enhanced by
matching the output nonlinearity to the source statistics, and (ii)
employing a linear term within the output nonlinearity, such as
that used in the constant-modulus algorithm, can improve these algorithms'
performances if certain aspects of the extracted sources' statistics
are known. Simulations verify the accuracy of the theoretical results.
page 34: Session TA3
TA3-1 Missing authors
The authors are:
Walter Willinger, Anna Gilbert and Anja Feldmann, ATT Research
not just Walter Willinger
TA3-6 Missing author
The authors are:
Mohammed Nafie and Ahmed H. Tewfik, Univ of Minnesota
not just Ahmed Tewfik.
Session TP2, paper 2: updated title and abstract:
Direct Semi-Blind Symbol Estimation for Multipath Channels
A. Lee Swindlehurst
Brigham Young University
A number of recent papers have treated the problem of channel
estimation when known training data is present. The unknown part of
the signal is typically estimated in an independent step, where the
channel inverse is applied to the received data. In this paper, a
technique is presented for directly estimating the unknown symbols
in a block of data that also contains training information. The
channel matrix can also be simultaneously estimated, provided the
channel lengths are not too long. The proposed method is
implemented in the frequency domain, and works best in situations
where the training data acts to convert the linear convolution of
the channel into circular convolution (as with a cyclic prefix in
multicarrier systems). However, reasonable results are still
obtained asymptotically even without this constraint.
page 46: session TP6
TP6-3 title should read:
"Computational Convexity and the Hyperspectral Mixed Pixel
Problem"
Session TP3:
Paper TP3-1 is withdrawn
Session TP5: chair: Nasir Memon
Polytechnic University, Brooklyn, NY
Paper TP5-4: new paper title:
Recent Advances in Embedded Lossless Image Coding via
Reversible Transforms,
Xiaolin Wu, Univ. of Western Ontario
Paper TP5-5: New paper title
Image Compression with EBCOT (Embedded Block Coding with
Optimized Truncation)
David Taubman, HP Labs.
page 49: Session TP7
TP7-1 : both title and author info are incorrect.
The correct details are:
Title:
"Model Fitting and Testing in Near Surface Seismics Using Maximum
Likelihood in Frequency Domain."
Authors:
Johann F. B"ohme and Markus Westebbe, Ruhr University Bochum, and
Heinrich Krummel, THOR Kiel.
TP7-2: missing author
the authors are :
Z. Nan and A. Nehorai.
TP7-4: incorrect title
the correct title is:
"Parallels Between Multipath Signal Processing in Underwater Acoustics
and Over-the-Horizon Shortwave Radar"
TP7-5 incorrect title
the correct title is:
"The Theoretical Performance of a class of Space-Time Adaptive
Detection and Training Strategies for Airborne Radar"
TP7-8 paper should be swapped with WA2-7
The current paper TP7-8
``A computationally efficient method for joint direction
finding and frequency estimation for colored noise''
by Mats Viberg, Chalmers University of Technology
and Petre Stoica, Uppsala University
should be swapped with WA2-7
``Spatio-temporal array processing for CDMA/SDMA downlink
transmission'',
by Giuseppe Montalbano, Politecnico di Torino & Institut Eurecom,
Irfan Ghauri and Dirk T.M. Slock, Institut Eurecom.
page 52: Session TP8b : wrong chair
The chair is Stella N. Batalama at the
State University of New York at Buffalo
(not J. Li at Univ Florida).
Session WA4: chair to be determined
=========================================================================
Other changes:
(1) The abstract for paper MP8b-12 has been updated.
Here's the full information
Numerical Solutions for Optimum Distributed Detection of Known Signals
in Dependent t-Distributed Noise---the Two Sensor Problem
X. Lin and R. S. Blum
Electrical Engineering and Computer Science Dept.
Lehigh University
19 Memorial Drive West
Bethlehem, PA 18015-3084
We examine the two-sensor distributed detection problem for detecting a
known signal in t-distributed noise which is dependent from sensor to
sensor. The t-distributions include Gaussian, Cauchy and a number of
other interesting distributions with tails between Gaussian and Cauchy.
A Gauss-Seidel algorithm which attempts to minimize the Bayes risk is
used to obtain the best sensor decision regions. The properties of the
best sensor decision regions are predicted based on the problem's
parameters. All nonrandomized fusion rules are considered. In some
specific cases the optimum distributed detection sensor rules are shown
to perform better than the best likelihood ratio tests by Monte Carlo
simulations.
contact author:
R. S. Blum
Electrical Engineering and Computer Science Dept.
Lehigh University
19 Memorial Drive West
Bethlehem, PA 18015-3084
Email: rblum@eecs.lehigh.edu
(610) 758-3459 Fax: (610) 758-6279
(2) The contact author of paper MP8b has moved.
Ppaer MP8b is
Order Statistics Based Diversity Combining For Fading Channels
by
S. Gollakota and R. Viswanathan
The contact author's new co-ords are:
Dr. R. Viswanathan
Professor
Division of Engineering
University of Texas at San Antonio
6900 North Loop 1604 West
San Antonio, Texas 78249-0665
Ph: 210-458-7517
Fax: 210-458-5589
e-mail: viswa@voyager1.utsa.edu
(3) The contact author for paper MP8b-11,
``Adaptive data fusion processing: thoughts and perspectives''
by James Llinas and Tarun Sing
will be Dr. Tarun Singh
tsingh@eng.buffalo.edu
ph 716-645-2593 ext 2255
(4) Titles and abstracts for paper TP8a-2 have been updated, the
correct information follows:
Robust Matched Subspace Detection and Estimation
Todd McWhorter and Michael Clark
Mission Bay Research Inc., Monterey, CA
In this paper we derive robust estimators of the parameters in a
linear subspace model. Like total least squares (TLS), these
estimators allow for errors in both the data and in the subspace
model. However, unlike total least squares, these estimators allow
the perturbation of the model to be constrained. These constraints
have simple geometric interpretations and allow for various levels of
confidence in the a priori signal model. These estimators are also
distinguished from TLS in that they are invariant to certain arbitrary
scalings and rotations of the signal model. This property, which TLS
does not possess, is shown to be essential for certain estimation
problems. We apply these estimators to the matched subspace detection
problem and illustrate, by way of example, that the resulting
detectors are robust.
(5) Paper title for MA2b-5 has changed to:
Decision Feedback Equalization for Volterra Systems - A Root Method
by Arthur Redfern and G. Tong Zhou
Georgia Tech, Atlanta, GA
The need to recover the original input from the output of a nonlinear system
is a problem common to many applications. In this paper, we propose a
Volterra decision feedback equalizer that is based on finding the roots of a
polynomial function of the input. It is capable of equalizing severely
nonlinear systems under the assumption that the input comes from a finite
symbol set. A modification is also proposed which allows for the extension
of the root method to baseband Volterra systems with complex inputs and the
analysis of the effects of noise on the current symbol estimate.
Simulations demonstrate the performance of the proposed algorithm.
(6) Paper Wa8a-14 correct information should read:
Ali H. Sayed and S. Chandrasekaran, "Estimation in the Presence of
Multiple Sources of Uncertainties with Applications"