Plenary lectures

Multi-way Blind Source Separation Using Nonnegative Matrix Factorization and Sparse Component Analysis

Tuesday, September 4th, just after opening ceremony at 9:00 - Sala Kongresowa (Congress Hall)

Andrzej Cichocki, RIKEN Laboratory, Japan


Nonnegative matrix factorization (NMF), Non-negative tensor factorization (NTF), parallel factor nalysis PARAFAC and TUCKER models with non-negativity constraints have been recently proposed as promising sparse and quite efficient representations of signals, images, or general data. From a viewpoint of multidimensional data analysis, NTF is very attractive because it takes into account spatial and temporal correlations between variables more accurately than 2D matrix factorizations, such as NMF or ICA and it provides usually sparse common factors or hidden (latent) components with physical or physiological meaning and interpretation. In this talk we review several general and flexible models with multilayer or recurrent structures. Especially, we discuss 3D tensors (also known as n-way arrays or multidimensional arrays) factorizations and discuss some potential applications ranging from neuroscience and bioinformatics. Application to biomedical signal processing and Brain Machine Interface (BMI) will be also briefly presented. We will present a new 3D tensor modeling (decomposition/factorization) approach and associated learning algorithms in applications to multi-way Blind Source Separation (BSS), multidimensional data analysis, and sparse image representations. Using generalized cost functions (alpha and beta divergences), we will present derivation and practical implementations of three classes of algorithms: Multiplicative, Fixed Point Alternating Least Squares (FPALS) and Alternating Interior-Point Gradient (AIPG) algorithms. Some of the proposed algorithms are characterized by improved efficiency and convergence rates and can be applied with various distributions of data and additive noise. We discuss various cost functions used in information theory, which allows us to obtain generalized forms of learning algorithms. We have confirmed by extensive simulations that our multilayer NTF approach with multi-start initializations improves performance of the proposed algorithms if a specific model is approximately valid. In this talk, we will also discuss briefly some alternative approaches and algorithms for blind signal decomposition, especially for ICA, and SCA in order to estimate unknown sources signals, to perform feature extraction, dimension reduction and object recognition, remove artifacts and denoising of multi-modal, multi-sensory data.



Andrzej Cichocki received the M.Sc. (with honors), Ph.D. and Dr.Sc. (Habilitation) degrees, all in electrical engineering. from Warsaw University of Technology (Poland). Since 1972, he has been with the Institute of Theory of Electrical Engineering, Measurement and Information Systems, Faculty of Electrical Engineering at the Warsaw University of Technology, where he obtained a title of a full Professor in 1995. He spent several years at University Erlangen-Nuerenberg (Germany), at the Chair of Applied and Theoretical Electrical Engineering directed by Professor Rolf Unbehauen, as an Alexander-von-Humboldt Research Fellow and Guest Professor. In 1995-1997 he was a team leader of the laboratory for Artificial Brain Systems, at Frontier Research Program RIKEN (Japan), in the Brain Information Processing Group. He is currently the head of the laboratory for Advanced Brain Signal Processing, at RIKEN Brain Science Institute (JAPAN) in the Brain-Style Computing Group directed by Professor Shun-ichi Amari. He is co-author of more than 200 technical papers and three internationally recognized monographs (two of them translated to Chinese): Adaptive Blind Signal and Image Processing (Wiley, April 2003-revised edition), CMOS Switched-Capacitor and Continuous-Time Integrated Circuits and Systems (Springer-Verlag, 1989) and Neural Networks for Optimizations and Signal Processing (Teubner-Wiley, 1994). He is Editor in Chief of International Journal Computational Intelligence and Neuroscience and Associate Editor of IEEE Transactions on Neural Networks.

Channel-Aware Distributed Estimation and Detection Using Wireless Sensor Network

Tuesday, September 4th, 14:00 - Sala Kongresowa (Congress Hall)

Georgios B. Giannakis, University of Minnesota, USA


Outline of Topics:
1. Motivation and Context
1a. Energy and Bandwidth Constraints
1b. Applications
2. Distributed Detection and Estimation
2a. Universal and Channel-Aware Detection
2b. Parameter Estimation and Tracking
2c. Dimensionality Reduction and Compression
2d. Performance and Distortion-Rate Analyses
3. Wireless Communication Issues
3a. Synchronization Algorithms
3b. Channel-Aware Detection and Estimation
3c. Multiple Access and Resource Allocation
4. Networking Issues
5. Summary and Future Directions




G. B. Giannakis (Fellow'97) received his Diploma in Electrical Engr. from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. Since 1999 he has been a professor with the ECE Department at the Univ. of Minnesota, where he now holds an ADC Chair in Wireless Telecommunications.
His general interests span the areas of communications, networking and statistical signal processing - subjects on which he has published more than 250 journal papers, 450 conference papers, two edited books and two research monographs. Current research focuses on diversity techniques, complex-field and space-time coding, multicarrier, cooperative wireless communications, cognitive radios, cross-layer designs, mobile ad hoc networks, and wireless sensor networks.
G. B. Giannakis is the (co-) recipient of six paper awards from the IEEE Signal Processing (SP) and Communications Societies including the G. Marconi Prize Paper Award in Wireless Communications. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), a Young Faculty Teaching Award and the G. W. Taylor Award for Distinguished Research from the University of Minnesota. An IEEE Fellow he has served the IEEE in various posts.

Reinventing Compression: The New Paradigm of Distributed Video Coding

Wednesday, September 5th, 13:30 - Sala Kongresowa (Congress Hall)

Bernd Girod, Stanford University, USA


Distributed coding is a new paradigm for video compression, based on Slepian and Wolf's and Wyner and Ziv's information-theoretic results from the 1970s. This talk reviews the recent development of practical distributed video coding schemes. Wyner-Ziv coding, i.e., lossy compression with receiver side information, enables low-complexity video encoding where the bulk of the computation is shifted to the decoder. Since the interframe dependence of the video sequence is exploited only at the decoder, an intraframe encoder can be combined with an interframe decoder. Wyner-Ziv coding is also naturally robust against transmission errors and can be used for joint source-channel coding by protecting the signal waveform rather than a compressed bit-stream. It thus achieves graceful degradation under deteriorating channel conditions without a layered signal representation. Besides low-complexity encoding and robust transmission, the distributed coding paradigm enables novel solutions to diverse problems ranging from coding for random access to media authentication to compression of encrypted signals.



Bernd Girod is Professor of Electrical Engineering and (by courtesy) Computer Science in the Information Systems Laboratory of Stanford University, California. He was Chaired Professor of Telecommunications in the Electrical Engineering Department of the University of Erlangen-Nuremberg until 1999. His research interests are in the areas of video compression and networked media systems, and he has published over 400 conference and journal papers, as well as 5 books. Professor Girod has been involved with several startup ventures as founder, director, investor, or advisor, among them Polycom (Nasdaq:PLCM), Vivo Software, 8x8 (Nasdaq: EGHT), and RealNetworks (Nasdaq: RNWK). Since 2004, he serves as the Chairman of the new Deutsche Telekom Laboratories in Berlin. He received the Engineering Doctorate from University of Hannover, Germany, and an M.S. Degree from Georgia Institute of Technology. Prof. Girod is a Fellow of the IEEE and a member of the German Academy of Sciences (Leopoldina). He received the 2002 EURASIP Best Paper Award, the 2004 EURASIP Technical Achievement Award, and the 2007 IEEE Multimedia Communication Best Paper Award.

EQUALIZATION OF MIMO CHANNELS

Thursday, September 6th, 13:30 - Sala Kongresowa (Congress Hall)

John G. Proakis, University of California, USA


We consider the equalization of multiple-input, multipleoutput (MIMO) wireless communication systems that employ multiple transmit and receive antennas to increase the data rate and achieve signal diversity in fading multipath channels. Two scenarios in the equalization of MIMO systems are treated. The first is a point-to-point MIMO system in which the channel characteristics are known at the receiver only and, hence, the equalization is performed at the receiver. The second is a point-to-multipoint (broadcast) MIMO system in which the channel characteristics are known at the transmitter. In this case, the equalization is performed at the transmitter. Both linear and nonlinear equalization algorithms are treated.



John Proakis (S'58-M'62-F'84-LF'99) received the BSEE from the University of Cincinnati in 1959, the MSEE from MIT in 1961 and the Ph.D. from Harvard University in 1967. He is an Adjunct Professor at the University of California at San Diego and a Professor Emeritus at Northeastern University. He was a faculty member at Northeastern University from 1969 through 1998 and held the following academic positions: Associate Professor of Electrical Engineering, 1969-1976; Professor of Electrical Engineering, 1976-1998; Associate Dean of the College of Engineering and Director of the Graduate School of Engineering, 1982-1984; Interim Dean of the College of Engineering, 1992-1993; Chairman of the Department of Electrical and Computer Engineering, 1984-1997. Prior to joining Northeastern University, he worked at GTE Laboratories and the MIT Lincoln Laboratory.

His professional experience and interests are in the general areas of digital communications and digital signal processing. He is the author of the book Digital Communications (New York: McGraw-Hill, 2001, fourth edition), and co-author of the books, Introduction to Digital Signal Processing (Upper Saddle River: Prentice Hall, 2007, fourth edition); Digital Signal Processing Laboratory (Englewood Cliffs: Prentice Hall, 1991); Advanced Digital Signal Processing (New York: Macmillan, 1992); Algorithms for Statistical Signal Processing(Upper Saddle River: Prentice Hall, 2002);Discrete-Time Processing of Speech Signals (New York: Macmillan, 1992, IEEE Press, 2000); Communication Systems Engineering, (Upper Saddle River: Prentice Hall, 2002, second edition); Digital Signal Processing Using MATLAB V.4 (Boston: Brooks/Cole-Thomson Learning, 2007, second edition); Contemporary Communication Systems Using MATLAB (Boston: Brooks/Cole-Thomson Learning, 2004, second edition); Fundamentals of Communication Systems (Upper Saddle River: Prentice Hall , 2005)

Recent Advances in Video Coding and Transmission

Friday, September 7th, 9:00 - Sala Kongresowa (Congress Hall)

Thomas Wiegand, Fraunhofer Institute for Telecommunications, Germany


Higher compression gains, improved error robustness, increased adaptability and more functionality in light of the continuous evolution of networks and end devices are the most challenging factors of modern video coding and transmission. This talk aims to address those aspects by discussing the current state of H.264/AVC video coding standardization and its upcoming extensions together with the technical ecosystem and related research. For H.264/AVC, the state-of-the-art is reviewed and new optimization approaches for encoders as well as new techniques for enhanced video compression are discussed.

One new extension of H.264/AVC is called Multi-view Video Coding (MVC) to efficiently represent video signals simultaneously acquired by multiple cameras. MVC aims at applications such as 3D Television and Free Viewpoint Video. These new applications enable new user experiences including stereoscopic and head motion parallax viewing as well as free viewpoint navigation through scenes. Also alternative techniques such as single/multi-view plus depth and computer graphics compression are analyzed.

Another extension of H.264/AVC is scalable video coding. Modern video transmission systems using the Internet and mobile networks are typically characterized by a wide range of connection qualities and receiving devices. Scalable video coding providing adaptation to error rates, throughput, power resources and spatial formats is a highly attractive option for modern video transmission applications as will be shown. These functionalities provide enhancements to transmission applications such as video streaming over 3GPP mobile, ad-hoc and peer-to-peer networks, mobile TV, as well as video conferencing.



Thomas Wiegand is the head of the Image Communication Group in the Image Processing Department of the Fraunhofer Institute for Telecommunications - Heinrich Hertz Institute Berlin, Germany. He received the Dipl.-Ing. degree in Electrical Engineering from the Technical University of Hamburg-Harburg, Germany, in 1995 and the Dr.-Ing. degree from the University of Erlangen-Nuremberg, Germany, in 2000. His research interest include video processing and coding, multimedia transmission, semantic image representation, as well as computer vision and graphics.
From 1993 to 1994, he was a Visiting Researcher at Kobe University, Japan. In 1995, he was a Visiting Scholar at the University of California at Santa Barbara, USA. From 1997 to 1998, he was a Visiting Researcher at Stanford University, USA and served as a consultant to 8x8, Inc., Santa Clara, CA, USA. He is currently a member of the technical advisory boards of the two start-up companies Layered Media, Inc., Rochelle Park, NJ, USA and Stream Processors, Inc., Sunnyvale, CA, USA.
Since 1995, he is an active participant in standardization for multimedia with successful submissions to ITU-T VCEG, ISO/IEC MPEG, 3GPP, DVB, and IETF. In October 2000, he was appointed as the Associated Rapporteur of ITU-T VCEG. In December 2001, he was appointed as the Associated Rapporteur / Co-Chair of the JVT. In February 2002, he was appointed as the Editor of the H.264/AVC video coding standard and its extensions (FRExt and SVC). In January 2005, he was appointed as Associated Chair of MPEG Video.
In 1998, he received the SPIE VCIP Best Student Paper Award. In 2004, he received the Fraunhofer Award for outstanding scientific achievements in solving application related problems and the ITG Award of the German Society for Information Technology. Since January 2006, he is an Associate Editor of IEEE Transactions on Circuits and Systems for Video Technology.

3-D Displays and Signal Processing: An Answer to 3-D Ills?

Friday, September 7th, 13:30 - Sala Kongresowa (Congress Hall)

Janusz Konrad, Boston University, USA


Three-dimensional perception of our surroundings is a natural part of daily life. Over the last 100+ years many attempts have been made to replicate the 3-D experience by means of various photo-, film- or print-based systems. While some have achieved limited commercial success, none have attained equal status to their 2-D counterparts. However, recent advances in electronic display technologies, digital signal processing techniques and computer graphics tools, promise a new era for 3-D displays. In fact, signal processing algorithms tuned to the unique problems of 3-D imaging will likely be the enabling technology for the emerging 3-D display systems.

In this talk. I will discuss the major 3-D display technologies in use today, from simple glasses-based systems (colored, polarized, shuttered), through glasses-free parallax-barrier and microlens displays, to holographic, and volumetric display devices. I will describe the underlying physics as well as the associated benefits and deficiencies. I will emphasize the common principles that all 3-D displays share, and discuss issues such as sampling, multiplexing and rendering, particularly critical to dynamic 3-D display systems. I will highlight the role signal processing has played in addressing deficiencies of some 3-D displays, and will also point out the still unsolved problems awaiting signal processing solutions.



Janusz Konrad received M.Eng.degree from the Technical University of Szczecin, Poland in 1980, and the Ph.D. degree from McGill University, Montréal, Canada, in 1989. From 1989 to 2000 he was with INRS-Télécommunications (University of Québec), Montréal. Since 2000 he has been an Associate Professor at the Department of Electrical and Computer Engineering, Boston University. In the past, he collaborated with Imax Corporation, Bell-Northern Research, Digital Equipment Corp., and EMC Corp. He was an Associate Editor for the IEEE Transactions on Image Processing and IEEE Signal Processing Letters, as well as Technical Program Co-Chair for the IEEE International Conference on Image Processing (ICIP-2000), and Tutorials Co-Chair for the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-2004), and member of the Image and Multidimensional Signal Processing Technical Committee of the IEEE Signal Processing Society. Currently, he is an Associate Technical Editor for IEEE Communications Magazine, Associate Editor for EURASIP Journal on Image and Video Processing, and a program committee member of several international conferences and workshops. He is a co-recipient, jointly with Dr. N. Božinović, of the 2004-2005 EURASIP Image Communication Best Paper Award and the IEEE 2001 Signal Processing Magazine award for a paper co-authored with Dr. C. Stiller. His interests are in the areas of image and video compression and processing, stereoscopic and 3-D imaging, multidimensional signal processing and computer vision.