Sparsity-Aware Data-Selective LearningDate: 2014-10-14 Add to Google Calendar
Time: 1:30-2:30 pm
Location: Holmes Hall 388
Speaker: Prof. Paulo S.R. Diniz, Universidade Federal do Rio de Janeiro
This presentation addresses fundamental, as well as some advanced concepts that are important to understand the principles of data-selective algorithms. These type of algorithms utilize environment data for updating only when they bring new information. As a result the obtained parameter estimations become more accurate without sacrificing the learning speed. The data-selective algorithm are specially suitable for applications where computational resources are limited and/or power saving is a requirement. Typical examples are many communication systems where the growing demand for services has increased the interest in employing adaptive techniques as part of the receivers.
In other modern communication systems, such as wireless and multiuser systems, there are two major sources of interference: intersymbol interference due to multipath fading and co-channel interference due to multiple-user communications. In addition, in a wireless system such as land mobile radio, the fast time-varying fading calls for adaptive solutions. Recent studies have also shown that sensor arrays is another application where the data-selective algorithms will play a key role, given the limited power resources and transmission bandwidth of the sensors.
We present two adaptive filtering algorithms that combine a sparsity-promoting scheme with a data-selection mechanism. Sparsity is promoted via approximations to the 10 norm in order to increase convergence speed of the algorithms when dealing with sparse/compressible signals. These approximations circumvent some difficulties of working with the 10 norm, thus allowing the development of online algorithms. Data selection is implemented based on set-membership filtering, which yields robustness against noise and reduced computational burden. The proposed algorithms are analyzed in order to set properly their parameters to guarantee stability. In addition, we characterize their updating processes from a geometrical viewpoint. Simulation results show that the proposed algorithms outperform the state-of-the-art algorithms designed to exploit sparsity.
Paulo S. R. Diniz was born in NiterŽoi, Brazil. He received the Electronics Eng. degree (Cum Laude) from the Federal University of Rio de Janeiro (UFRJ) in 1978, the M.Sc. degree from COPPE/UFRJ in 1981, and the Ph.D. from Concordia University, Montreal, P.Q., Canada, in 1984, all in electrical engineering.
Since 1979 he has been with the Department of Electronic Engineering (the undergraduate dept.) UFRJ. He has also been with the Program of Electrical Engineering (the graduate studies dept.), COPPE/UFRJ, since 1984, where he is presently a Professor. He served as Undergraduate Course Coordinator and as Chairman of the Graduate Department. He is one of the three senior researchers and coordinators of the National Excellence Center in Signal Processing. He has also received the Rio de Janeiro State Scientist award, from the Governor of Rio de Janeiro state.
From January 1991 to July 1992, he was a visiting Research Associate in the Department of Electrical and Computer Engineering of University of Victoria, Victoria, B.C., Canada. He also holds a Docent position at Helsinki University of Technology. From January 2002 to June 2002, he was a Melchor Chair Professor in the Department of Electrical Engineering of University of Notre Dame, Notre Dame, IN, USA. His teaching and research interests are in analog and digital signal processing, adaptive signal processing, digital communications, wireless communications, multirate systems, stochastic processes, and electronic circuits. He has published over 280 refereed papers in some of these areas and wrote ADAPTIVE FILTERING: Algorithms Practical Implementation, Springer, Fourth Edition 2013, and DIGITAL SIGNAL PROCESSING: System Analysis and Design, Cambridge University Press, Cambridge, UK, Second Edition 2010 (with E. A. B. da Silva and S. L. Netto) and the monograph BLOCK TRANSCEIVERS: OFDM and Beyond, Morgan & Claypool, New York, NY, 2012 (W. A. Martins, and M. V. S. Lima).
He was the General Co-Chair of the 2011 IEEE International Symposium on Circuits and Systems held in Brazil. He has served Vice President for region 9 of the IEEE Circuits and Systems Society and as Chairman of the DSP technical committee of the same Society. He is also a Fellow of IEEE (for fundamental contributions to the design and implementation of fixed and adaptive filters and Electrical Engineering Education). He has served as associate editor for the following Journals: IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing from 1996 to 1999, IEEE Transactions on Signal Processing from 1999 to 2002, and the Circuits, Systems and Signal Processing Journal from 1998 to 2002. He was a distinguished lecturer of the IEEE Circuits and Systems Society for the year 2000 to 2001. In 2004 he served as distinguished lecturer of the IEEE Signal Processing Society and received the 2004 Education Award of the IEEE Circuits and Systems Society. He also holds some best-paper awards from conferences and from an IEEE journal. In 2014, he received the Charles A. Desoer Technical Achievements Award from the IEEE Circuits and Systems Society.