Published March 2011
| public
Journal Article
Learning Low-Dimensional Signal Models
Abstract
Sampling, coding, and streaming even the most essential data, e.g., in medical imaging and weather-monitoring applications, produce a data deluge that severely stresses the available analog-to-digital converter, communication bandwidth, and digital-storage resources. Surprisingly, while the ambient data dimension is large in many problems, the relevant information in the data can reside in a much lower dimensional space.
Additional Information
© 2011 IEEE. Date of publication: 17 February 2011. Many graduate students contributed to the ideas and results reviewed in this article. The authors particularly acknowledge the contributions of Minhua Chen, Armin Eftekhari, John Paisley, and Mingyuan Zhou. The authors also thank the reviewers for a careful reading of the original version of this article and suggestions that led to a significantly improved final article.Additional details
- Eprint ID
- 22840
- Resolver ID
- CaltechAUTHORS:20110314-091724983
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2011-03-16Created from EPrint's datestamp field
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2021-11-09Created from EPrint's last_modified field