13th IEEE DIgital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop

Keynote Talks

The keynote speakers this year are: Dr. Arthur B. Baggeroer, Dr. John H. Cozzens, Dr. Alfred O. Hero III, Dr. José M. F. Moura, and Dr. John A. Tague. Dr. Arthur Baggeroer's keynote is entitled "Vector Sensor Arrays, Adaptive Processing and the Snapshot Problem". Dr. John H. Cozzen's keynote is entitled "Signal Processing, the Stealth Technology". Dr. Alfred Hero's keynote is entitled "R'enyi entropies for statistical signal processing". Dr. José M. F. Moura's keynote is entitled "Distributed Algorithms in Sensor Networks". Dr. Tague's keynote is entitled "Undersea Signal Processing at the Office of Naval Research: A Status Report". We are excited to have these speakers at our conference.

Dr. Arthur B. Baggeroer

Vector sensor arrays (VSA's) have been used for several decades in areas such as geophysics (well logging, 4D seismics, earthquakes), oceanogra- phy (current meters), dual polarization radars and acoustics (vertical arrays of DIFAR sonobuoy). Towed vector sensor arrays are also evolv- ing with new solid state technology. The signal processing literature on VSA's is very extensive; however, most papers focus on ideal arrays with ensemble covariances. When applied to experimental data one must confront sensor mismatch, the impact of position and orientation errors and most importantly the so called "snapshot" issue for arrays with a "significant" number of sensors. The last problem is especially important when using adaptive processing methods in a nonstationary, e.g. moving source environment. In ocean acoustics and bottom geophysics one uses four component sensors - one for pressure and three for the vector velocity. One then has four times as many sensors as with the hydrophone arrays now used, so one might claim that the usual guidelines based on sensor count must be multiplied by a factor of four; however, in directional fields the number of signals remain the same. Consequently, methods based on eigen analysis should reflect the number of sources, or significant eigenvalues albeit with a much larger background eigenvalues since the total depends upon sensor count. In addition, pressure and velocity are coupled by the acoustic momentum equation, so there is an implicit re duction in the effective rank of any sample covariance matrix. This in turn is complicated by the propagation since the momentum equation is part of derivation of the wave equation. In this presentation we explore adaptive methods and the "snapshot" issue for VSA's. This done for both free space and waveguide prop- agation. Receivers which identify the partition and coupling of the pressure and velocity signals are introduced and examples presented. Finally, we use recent results from random matrix theory to identify the effective number of sources which can be discerned with a finite number of "snapshots."

Biography:

Arthur B. Baggeroer is a Ford Professor of Engineering in the Departments of Mechanical Engineering and Electrical Engineering & Computer Science at the Massachusetts Institute of Technology. He received the degrees of B.S.E.E. from Purdue University in 1963 and Sc.D. from MIT in 1968. He was been a consultant to the Chief of Naval Research at the NATO SACLANT Center (now NURC) in 1977 and a Cecil and Ida Green Scholar at the Scripps Institution of Oceanography in 1990 while on sabbatical leaves. He is a Fellow of the IEEE and the Acoustical Society of America. He received the IEEE Oceanic Engineering Society Distinguished Technical Achievement Award in 1991, was an elected member of the Executive Council of the Acoustical Society from 1994-1997, and was awarded the Rayleigh-Helmholtz Medal from the Acoustical Society in 2003. He was elected to the National Academy of Engineering in 1995 and awarded a Secretary of the Navy / Chief of Naval Operations Chair in Oceanographic Science in 1998. He serves as a senior advisor to the Navy on numerous committees and panels. He recently chaired the NSB panel on Distributed Remote Surveillance. Prof. Baggeroer was awarded the "Distinguished Alumni Award" of the Dept. of Electrical and Computer Engineering from his alma mater Purdue University. He was recently awarded the ADM Charles Martel - David Bushnell Award by NDIA for "outstanding technical contributions to the defense of the US in the field of Undersea Warfare." He has been chief scientist on fifteen oceanographic cruises with seven in the Arctic Ocean. His research has concerned signal and array processing for sonar, radar and seismic systems, ocean acoustic telemetry, global acoustics for ocean thermometry and matched field array processing. He also has had long affiliations with the Woods Hole Oceanographic Institution where he was Director of the MIT - Woods Hole Joint Program from 1983 - 1988 and the MIT - Lincoln Laboratory. Finally, he was elected four times to be a member of the School Committee for the Town of Westwood, MA (1978 - 1990) and was elected to be chairman four times. Some of the Navy Committees he has been involved are: i) the Naval Studies Board, ii) the Ocean Studies Board both for six years), iii) the Submarine Superiority Technical Advisory Group (He was a member of the original committee for ADM Demars which eventually led to the submarine APB/ARCI processing system.), iv) the Fixed Surveillance Systems Technical Advisory Group; v) the SSIPT for N84 (twice), vi) the "'Red Team' for the Way Ahead for ASW study", vii) an panel member for many highly programs for the Navy and DARPA, viii) the Naval Research Advisory Committee (NRAC).

Dr. John H. Cozzens

This talk will attempt to provide a glimpse into the future: brief previews of the "new" Computing and Communication Foundations (CCF) Division and the "new" Theoretical Foundations Clusters, and (less briefly) how, from the vantage point of the Signal Processing Systems Program, the discipline called Signal Processing appears to be evolving and why.

Biography:

Dr. John H. Cozzens received a BA in mathematics from Temple University in 1966, and a PhD (also in mathematics) from Rutgers University in 1969. Before joining NSF in 1991, Cozzens was a Lead Scientist with the MITRE Corporation in Bedford MA, where he worked in a variety of areas. These included (algebraic) coding theory, residue number system arithmetic, detection and estimation, radar signal processing, network survivability, and automatic target recognition. Before that, Cozzens taught mathematics for 11 years at the college level. During that period, his research interests included (non)commutative ring theory, homological algebra, and differential algebra. He is currently a program director in the Theoretical Foundations (TF) Cluster that resides within the Division of Computing and Communication Foundations (CCF). In addition running the Signal Processing Systems Program, he is revisiting some earlier unfinished work on simple Noetherian rings after a twenty five-year hiatus.

Dr. Alfred Hero

The R'enyi entropy is a generalization of the Shannon entropy that arises in many problems of statistical signal processing. We will present an overview of the fundamental role of R'enyi entropy in information complexity, source coding, and topological inference. Several applications will be discussed including anomaly detection, intrinsic complexity estimation and dimension classification.

Biography:

Alfred O. Hero III received the B.S. (summa cum laude) from Boston University (1980) and the Ph.D from Princeton University (1984), both in Electrical Engineering. Since 1984 he has been with the University of Michigan, Ann Arbor, where he is a Professor in the Department of Electrical Engineering and Computer Science and, by courtesy, in the Department of Biomedical Engineering and the Department of Statistics. He has held visiting positions at Massachussets Institute of Technology (2006), Boston University, I3S University of Nice, Sophia-Antipolis, France (2001), Ecole Normale Sup'erieure de Lyon (1999), Ecole Nationale Sup'erieure des T'el'ecommunications, Paris (1999), Scientific Research Labs of the Ford Motor Company, Dearborn, Michigan (1993), Ecole Nationale Superieure des Techniques Avancees (ENSTA), Ecole Superieure d'Electricite , Paris (1990), and M.I.T. Lincoln Laboratory (1987 - 1989). His recent research interests have been in areas including: inference for sensor networks, adaptive sensing, bioinformatics, inverse problems. and statistical signal and image processing. He is a Fellow of the Institute of Electrical and Electronics Engineers(IEEE), a member of Tau Beta Pi, the American Statistical Association(ASA), the Society for Industrial and Applied Mathematics (SIAM), and the US National Commission (Commission C) of the International Union of Radio Science (URSI). He has received a IEEE Signal Processing Society Meritorious Service Award (1998), IEEE Signal Processing Society Best Paper Award (1998), a IEEE Third Millenium Medal and a 2002 IEEE Signal Processing Society Distinguished Lecturership. He was President of the IEEE Signal Processing Society (2006-2007) and during his term served on the TAB Periodicals Committee (2006). He is currently a member of the TAB Society Review Committee (2008-2010).

Dr. José M. F. Moura

Sensor networks have a large number of sensors that monitor continuously the state of a possibly large scale system and collect large amounts of data. The sensors are inexpensive and operate under limited power, communication, and computational resources. A number of problems of interest, including distributed inference (like detection, estimation, or classification,) distributed localization, or several types of consensus algorithms can be cast within the same general framework. We present a stochastic approximation approach to study these problems under a broad set of network conditions - deterministic or random networks where communication links or channels may fail at random times, communications is synchronous or asynchronous, channels are noisy or noiseless, and data is analog or digital (quantized). Finally, we address tradeoffs among network and application parameters and their impact on resource allocation, convergence rate, and topology design.

Biography:

José M. F. Moura is a Professor at Carnegie Mellon University where he founded CenSCIR, the Center for Sensed Critical Infrastructure Research, and ICTI, the Information and Communication Technologies Institute that manages the 100 M$ CMU-Portugal Program. He holds a D.Sc. in EECS from MIT and an EE degree from IST (Lisbon, Portugal). His interests are in algebraic and statistical signal/ image processing. Current projects are on sensor networks and critical physical infrastructures, time reversal imaging, bioimaging, and intelligent compilers for signal processing applications. He is President of the IEEE Signal Processing Society. He was the Editor in Chief for the IEEE Transactions on Signal Processing and was on the Boards of the IEEE Proceedings and the ACM Sensors Journal. He is a Fellow of the IEEE and AAAS, and a corresponding member of the Academia das Ciências of Portugal. He received the IEEE 3rd Millennium Medal, the IEEE SPS Meritorious Service Award, an IBM Faculty Award, and the 2007 CMU's College of Engineering Outstanding Research Award.

Dr. John A. Tague

The Undersea Signal Processing Program develops and demonstrates advanced signal processing algorithms that improve the Navy's ability to conduct anti-submarine warfare with passive and active acoustics. Sonar signal processing draws upon classic digital signal processing, statistical decision theory, linear algebra, and underwater acoustic propagation physics to tease information from time series data collected by acoustic sensor arrays. We fund a diverse portfolio of projects that encompass a wide range of specific objectives, technical approaches, and technical maturity. There are many interesting problems that need to be solved, and funds are available to underwrite research and graduate student support at universities throughout the country.

Biography:

John A. Tague was born in Waukegan, Illinois on September 27, 1953. He earned a B.S. degree in Electrical Engineering at the University of Illinois at Urbana-Champaign in 1976 and a Ph.D. degree in Electrical Engineering from the Pennsylvania State University in 1987. He was commissioned as an Ensign in the United States Navy, attended Nuclear Power and Submarine School, and served as the Reactor Controls Assistant on the USS Kamehameha from 1977-1979. He taught Electrical Engineering at Ohio University from 1987-1998 and directed 3 Ph.D. and 7 M.S. students in a variety of signal processing research projects. Dr. Tague is currently the Team Leader of the Undersea Signal Processing Program at the Office of Naval Research, and is responsible for the U.S. Navy's basic research, applied research, and advanced development of new passive and active sonar signal processing algorithms. He is also an affiliate faculty member at George Mason University, where he has taught graduate-level courses in detection and estimation theory. Dr. Tague is an Associate Editor of the IEEE Transactions on Aerospace and Electronic Systems, a Senior Member of the IEEE, and a former member of the IEEE Signal Processing Society Sensor Array and Multichannel Signal Processing Technical Committee. He is a member of Eta Kappa Nu and Sigma Xi.