Spring Meeting 2011
The Spring 2011 Meeting will be held at 8:30 p.m. on Wednesday, May 11, in Room 3206 of the Norbert Wiener Center for Harmonic Analysis and Applications in the Mathematics building on the campus of the University of Maryland College Park.
The speaker will be Dr. Radu Balan, Associate Professor of Mathematics at UMCP. He will present a lecture entitled "Sparse Component Analysis: Use of Statistical Methods and Sparse Signal Representations in Convolutive Blind Source Separation Problems".
The dinner will be held at Adele's Restaurant in the University of Maryland Stamp Student Union. The dinner will start at 6:30 p.m.
You are cordially invited to attend the pre-lecture dinner with the speaker. See below for directions and parking information for the dinner and lecture.
The dinner is a good way to meet people who share your interest in mathematics and its applications. It will be held at Adele's Restaurant in the University of Maryland Stamp Student Union. The dinner will begin at 6:30 p.m.
The meal choices are: Chesapeake Alfredo ($31.25), Thai Chicken Pasta ($27.00), JD Salmon ($32.50) and Black Angus Burger ($21.70). The pricing is inclusive of salad, entree choice, a soft drink of choice, ice cream dessert, and tax and gratuity. Smith Island Cake may be added at an additional charge of $4.25. A selection of beer and wines will be available for purchase.
To attend the dinner, please send your entree choice along with a check for the appropriate amount (made out to SIAM Washington-Baltimore Section) early enough to be received by TUESDAY, MAY 3, 2011, to our Treasurer, Jeff Sieracki, PO Box 1011, College Park, MD, 20741.PLEASE include your full name and email address with your check so that we can send you a confirmation of your reservation. If you cannot get your check to him by that date and you still want to come to dinner, then please email him by Tuesday, May 3, 2011 at email@example.com. We can accommodate at most twenty-five diners on this occasion, so be sure to reserve in advance.
Title: Sparse Component Analysis: Use of Statistical Methods and Sparse Signal Representations in Convolutive Blind Source Separation Problems
Center for Scientific Computation and Mathematical Modeling
University of Maryland College Park
Abstract: Sparse Component Analysis represents an overlap of two problems (and methods) of Statistics/Computer Science/Electrical Engineering/Applied Mathematics: Independent Component Analysis (ICA), and Sparse Representations. Originally, the ICA problem is looking for decomposing a random d-vector into a linear composition of exactly d independent random variables: x = A.s, where A is dxd unknown mixing matrix, and s is the d-vector of independent components. The Blind Source Separation (BSS) problem is very similar to ICA, except that A may be a matrix of (convolutive) operators. In practice, people applied these solutions to different type of signals. In particular audio (speech) signals gave rise to what is also known as "the cocktail party problem".Interesting algorithms were also obtained on images, bio-medical signals (e.g. EEG, ERP, fMRI). Independent of this, the Sparse Representation problem tries to decompose a vector x into a linear combination of (possibly redundant) frame vectors using a smallest number of coefficients. My talk uses sparse representation hypotheses in order to solve a convolutive BSS, including estimating the number of source signals.
Please see the following websites:
The lecture hall, room 3206, is located on the third floor above the rotunda, one floor above the Norbert Wiener Center offices, in the Mathematics building. The Mathematics building is a 5 minute walk from the restaurant, so diners may park in either location.