BEGIN:VCALENDAR
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME;VALUE=TEXT:PlanIt Purple
VERSION:2.0
PRODID:-//PlanIt Purple//EN
BEGIN:VEVENT
STATUS:CONFIRMED
LAST-MODIFIED:20090521T124614
URL:http://www.northwestern.edu/nico/events/index.html#seminars
PRIORITY:0
CLASS:PUBLIC
UID:381564@northwestern.edu
SUMMARY:Wednesdays@NICO: Compressed Sensing and Its Application in Large Wireless Networks*
DESCRIPTION:Presentation by Dongning Guo - Electrical Engineering & Computer Science The Nyquist/Shannon sampling theorem states that any band-limited analog signal can be represented without any loss by its discrete samples taken at a frequency twice of its bandwidth\, whereas lower sampling rate induces irrecoverable loss. Intuitively\, an analog signal of bandwidth B has at most 2B degrees of freedom per second\, which implies that at least 2B measurements per second is necessary. What is ignored is the fact that most useful signals have sparse representation in certain domain\, and apparently much fewer degrees of freedom. In this talk\, we discuss the new compressed sensing paradigm where a few random linear measurements of a sparse signal is shown to be sufficient for recovering the signal. As an application\, we show that neighbor discovery in large wireless networks is a compressed sensing problem by nature. Besides the fundamental limits on the number of transmissions for accurate discovery\, we show a simple and effective non-coherent compressed sensing scheme\, which requires much fewer transmissions than conventional random-access schemes. *This work is done with EECS Ph.D. student Jun Luo. NICO Coffee Hour will follow for questions\, networking\, and collaboration. http://www.northwestern.edu/nico/events/index.html#seminars
DTSTART:20090527T120000
DTEND:20090527T140000
CREATED:20090130T000000
DTSTAMP:20090130T000000
SEQUENCE:0
LOCATION:Evanston
END:VEVENT
END:VCALENDAR