· 2012· Review
Compressed sensing : theory and applications
- 1,854citations
- 2012year
Short summary
This paper presents a detailed overview of compressed sensing, a novel signal acquisition and reconstruction technique that allows for signal recovery from far fewer samples than traditionally required.
AI-generated from the title and abstract; the full text is not read.
Key points
- Compressed sensing enables signal recovery from significantly fewer samples than traditional methods.
- The theory of compressed sensing relies on signal sparsity and incoherence with the sensing matrix.
- Reconstruction algorithms are crucial for recovering the original signal from incomplete measurements.
- Applications span diverse fields including imaging, communications, and radar.
AI-generated from the title and abstract; the full text is not read.
Abstract
A detailed presentation of compressed sensing by leading researchers, covering the most significant theoretical and application-oriented advances.
The authors' abstract, as published at the source., 2012 · DOI ↗
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Field: Computational Mechanics
Computational MechanicsEngineering