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Events for February 28, 2011
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Signal Recovery from Randomized Measurements Using Structured Sparsity Models
Mon, Feb 28, 2011 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Marco F. Duarte, IPAM Postdoctoral Fellow, Dept. of Computer Science, Duke University
Talk Title: Signal Recovery from Randomized Measurements Using Structured Sparsity Models
Abstract: We are in the midst of a digital revolution spawned by the proliferation of sensing devices with ever increasing fidelity and resolution. The resulting data deluge has motivated compression schemes that rely on transform coding, where a suitable transformation of the data provides a sparse representation that compacts the signal energy into a few transform coefficients. This standard approach, however, still requires signal acquisition at the full Nyquist rate, which cannot be achieved in many emerging applications using current sensing technology. The emerging acquisition paradigm of compressive sensing (CS) leverages signal sparsity for recovery from a small set of randomized measurements. The standard CS theory dictates that robust recovery of a K-sparse, N-length signal is possible from M=O(K log(N/K)) measurements. New sensing devices that implement this measurement process have been developed for applications including optical and seismic imaging, communications, and biosensing.
In this talk, we show that it is possible to substantially decrease the number of measurements M without sacrificing robustness by leveraging more concise signal models that go beyond simple sparsity and compressibility. We present a modified CS theory for structured sparse signals that exploits the dependencies between values and locations of the significant signal coefficients; we provide concrete guidelines on how to create new recovery algorithms for structured sparse signals with provable performance guarantees that require as few as M=O(K) measurements. We also review example applications of structured sparsity for natural images, signal ensembles, and multiuser detection.
Biography: Marco F. Duarte received the B.Sc. degree in computer engineering (with distinction) and the M.Sc. degree in electrical engineering from the University of Wisconsin-Madison in 2002 and 2004, respectively, and the Ph.D. degree in electrical engineering from Rice University, Houston, TX, in 2009. During 2009-2010, he was a Visiting Postdoctoral Research Fellow in the Program of Applied and Computational Mathematics at Princeton University. He is currently the NSF/IPAM Mathematical Sciences Postdoctoral Research Fellow in the Department of Computer Science at Duke University, where he works on applications of deterministic matrix constructions in compressive sensing devices.
Dr. Duarte received the Rice University Presidential Fellowship and the Texas Instruments Distinguished Fellowship in 2004, and the Hershel M. Rich Invention Award in 2007 for his work on the single pixel camera. He was a coauthor on a paper with Chinmay Hegde and Volkan Cevher that won the Best Student Paper Award at the 2009 International Workshop on Signal Processing with Adaptive Sparse Structured Representations (SPARS). His research interests include compressive sensing, low-dimensional signal models, dimensionality reduction, and distributed signal processing.
Host: Prof. Shrikanth Narayanan
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Mary Francis
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Computer Engineering Seminar
Mon, Feb 28, 2011 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Weikang Qian, University of Minnesota
Talk Title: Digital yet Deliberately Random: Synthesizing Logical Computation on Stochastic Bit Streams
Abstract: Most digital circuits process information deterministically as zeros and ones. For example, the arithmetic unit of a modern computer performs calculations on deterministic integer or floating-point values represented in binary radix. However, digital computation need not be deterministic. In my research, I consider an alternative paradigm: digital circuits that compute on stochastic sequences of zeros and ones. Such circuits can implement complex arithmetic operations with very simple hardware. Also they are highly tolerant of soft errors (i.e., bit flips). In the first part of my talk, I will present a general method for synthesizing combinational circuits that compute on stochastic bit streams. The method can be used to synthesize arbitrary polynomial functions. Through polynomial approximations, it can also be used to synthesize non-polynomial functions.
Schemes for probabilistic computation can exploit physical sources to generate random bit streams. Generally, each source has a fixed bias and so provides bits that have a specific probability of being one versus zero. If many different probability values are required, it can be difficult or expensive to generate all of these directly from physical sources. In the second half of my talk, I will describe techniques for synthesizing circuits that transform source probabilities into target probabilities, entirely through combinational logic. I will conclude my talk by discussing potential applications of the design methodology for emerging nanoscale technologies, such as nanowire crossbar arrays and carbon nanotubes.
Biography: Weikang Qian is a final-year Ph.D. student in the Department of Electrical and Computer Engineering at the University of Minnesota. He received his Bachelor of Engineering degree in Automation from Tsinghua University, Beijing, China, in 2006. He has research interests in diverse fields such as computer-aided design of integrated circuits, circuit design for emerging technologies, and fault-tolerant computing. In recognition of his doctoral research, he received the Doctoral Dissertation Fellowship at the University of Minnesota. One of his papers was nominated for the William J. McCalla Best Paper Award at the 2009 International Conference on Computer-Aided Design (ICCAD), a top conference in the field of electronic design automation.
Host: Sandeep Gupta
Location: Hughes Aircraft Electrical Engineering Center (EEB) -
Audiences: Everyone Is Invited
Contact: Estela Lopez
