On Location: Euclidean Distance Matrices, Theory, Algorithms, and ApplicationsTue, Sep 29, 2015, 4pm / 3-133
Professor of Engineering
École Polytechnique Fédérale de Lausanne
“Location, location, and location” are the three things that matter in real estate, as the saying goes. In many other areas as well, location is key, from indoor positioning, to calibration in source/receiver arrays, to crystallography, to name a few. And central to location in physical space are Euclidean distance matrices (EDMs). EDMs are matrices of squared distances between points. Despite the usefulness of EDMs, they seem to be insufficiently known or used in the signal processing and communication communities. Our goal is to correct this deficit in a short but comprehensive overview. The talk is based on an overview paper in the IEEE Signal Processing Magazine, where the code for all of described algorithms and to generate figures is available online at http://lcav.epfl.ch/ivan.dokmanic, in the spirit of reproducible research.
Martin Vetterli received an Electrical Engineering degree from ETHZ in 1981, an MS degree from Stanford in 1982, and a Doctorate degree from EPFL in 1986. He has held faculty positions at Columbia University, University of California at Berkeley and is currently Full Professor at EPFL. He has also held a number of other positions at EPFL. Since January 2013 he is President of the National Research Council of the Swiss National Science Foundation. His research is in the areas of electrical engineering, computer sciences and applied mathematics including wavelet theory and applications to compression and self-organized communications systems. He is the co-author of three textbooks, “Wavelets and Subband Coding”, “Signal Processing for Communications” and “Foundations of Signal Processing”. Professor Vetterli has received many awards for his research and was recently elected as a Foreign Member of the National Academy of Engineering.