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PRODID:IEEE vTools.Events//EN
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DTSTART:20200308T030000
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DTSTART:20191103T010000
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BEGIN:VEVENT
DTSTAMP:20191114T043437Z
UID:0FC0B9F0-330C-4E60-A290-0C62D247035D
DTSTART;TZID=America/Denver:20191113T173000
DTEND;TZID=America/Denver:20191113T200000
DESCRIPTION:Developing high-bandwidth sensing and high-resolution imaging s
 ystems requires facing significant Big Data challenges in sampling and com
 putation. Fortunately\, in many applications\, the signals of interest exh
 ibit a certain low-dimensional structure such as having a sparse spectrum.
  This structure makes possible a variety of techniques for sub-Nyquist sam
 pling\, reconstructing\, and better localizing parameters of interest in s
 uch signals using modern optimization-based algorithms. This overview talk
  will survey some of the core ideas underlying sparsity\, optimization\, a
 nd compressive sensing and highlight specific potential applications in el
 ectromagnetic contexts such as radar imaging\, spectrum monitoring\, and a
 rray processing.\n\nCo-sponsored by: Association of Old Crows - Mile High 
 Chapter\n\nSpeaker(s): Prof Mike Wakin\, \n\nAgenda: \n1730-1800: Networki
 ng\, food (pizza)\n1800-1900: Feature Presentation (times approximate\, mi
 ght start earlier)\n\nRoom: 162\, Bldg: Alderson Hall\, 1613 Illinois St.\
 , Golden\, Colorado\, United States\, 80401
LOCATION:Room: 162\, Bldg: Alderson Hall\, 1613 Illinois St.\, Golden\, Col
 orado\, United States\, 80401
ORGANIZER:milehighcrows@gmail.com
SEQUENCE:5
SUMMARY:Sparsity\, Optimization\, and Compressive Sensing for Electromagnet
 ic Spectrum Applications
URL;VALUE=URI:https://events.vtools.ieee.org/m/207933
X-ALT-DESC:Description: <br /><pre class="moz-quote-pre">Developing high-ba
 ndwidth sensing and high-resolution imaging systems requires facing signif
 icant Big Data challenges in sampling and \ncomputation. Fortunately\, in 
 many applications\, the signals of interest exhibit a certain low-dimensio
 nal structure such as having a sparse \nspectrum. This structure makes pos
 sible a variety of techniques for sub-Nyquist sampling\, reconstructing\, 
 and better localizing parameters \nof interest in such signals using moder
 n optimization-based algorithms. This overview talk will survey some of th
 e core ideas underlying \nsparsity\, optimization\, and compressive sensin
 g and highlight specific potential applications in electromagnetic context
 s such as radar \nimaging\, spectrum monitoring\, and array processing.</p
 re><br /><br />Agenda: <br /><p><strong>1730-1800: Networking\, food (pizz
 a)<br /></strong><strong>1800-1900: </strong><strong>Feature Presentation 
 (times approximate\, might start earlier)<br /></strong></p>
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