Sparsity, Optimization, and Compressive Sensing for Electromagnetic Spectrum Applications
Hosted by the IEEE Aerospace and Electronic Systems Society (AESS) Denver Chapter and the Association of Old Crows
Developing high-bandwidth sensing and high-resolution imaging systems requires facing significant Big Data challenges in sampling and computation. Fortunately, in many applications, the signals of interest exhibit a certain low-dimensional structure such as having a sparse spectrum. This structure makes possible a variety of techniques for sub-Nyquist sampling, reconstructing, and better localizing parameters of interest in such signals using modern optimization-based algorithms. This overview talk will survey some of the core ideas underlying sparsity, optimization, and compressive sensing and highlight specific potential applications in electromagnetic contexts such as radar imaging, spectrum monitoring, and array processing.
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- 1613 Illinois St.
- Golden, Colorado
- United States 80401
- Building: Alderson Hall
- Room Number: 162
- Click here for Map
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- Co-sponsored by Association of Old Crows - Mile High Chapter
- Starts 21 October 2019 04:29 AM UTC
- Ends 13 November 2019 07:30 PM UTC
- No Admission Charge
Speakers
Prof Mike Wakin of Colorado School of Mines
Sparsity, Optimization, and Compressive Sensing for Electromagnetic Spectrum Applications
Developing high-bandwidth sensing and high-resolution imaging systems requires facing significant Big Data challenges in sampling and computation. Fortunately, in many applications, the signals of interest exhibit a certain low-dimensional structure such as having a sparse spectrum. This structure makes possible a variety of techniques for sub-Nyquist sampling, reconstructing, and better localizing parameters of interest in such signals using modern optimization-based algorithms. This overview talk will survey some of the core ideas underlying sparsity, optimization, and compressive sensing and highlight specific potential applications in electromagnetic contexts such as radar imaging, spectrum monitoring, and array processing.
Biography:
Prof. Michael B. Wakin, Department of Electrical and Computer Engineering, Colorado School of Mines
Michael B. Wakin is a Professor of Electrical Engineering at the Colorado School of Mines. Dr. Wakin received a B.S. in electrical engineering and a B.A. in mathematics in 2000 (summa cum laude), an M.S. in electrical engineering in 2002, and a Ph.D. in electrical engineering in 2007, all from Rice University. He was an NSF Mathematical Sciences Postdoctoral Research Fellow at Caltech from 2006-2007, an Assistant Professor at the University of Michigan from 2007-2008, and a Ben L. Fryrear Associate Professor at Mines from 2015-2017. His research interests include signal and data processing using sparse, low-rank, and manifold-based models. In 2007, Dr. Wakin shared the Hershel M. Rich Invention Award from Rice University for the design of a single-pixel camera based on compressive sensing. In 2008, Dr. Wakin received the DARPA Young Faculty Award for his research in compressive multi-signal processing for environments such as sensor and camera networks. In 2012, Dr. Wakin received the NSF CAREER Award for research into dimensionality reduction techniques for structured data sets. In 2014, Dr. Wakin received the Excellence in Research Award for his research as a junior faculty member at Mines. Dr. Wakin is a recipient of the Best Paper Award from the IEEE Signal Processing Society. He has served as an Associate Editor for IEEE Signal Processing Letters and is currently an Associate Editor for IEEE Transactions on Signal Processing.
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Agenda
1730-1800: Networking, food (pizza)
1800-1900: Feature Presentation (times approximate, might start earlier)
After 5pm, visitors can park for free on the gray campus streets or colored lots indicated on the map.
However, street parking off campus (white areas) requires a Golden city permit.