# Michael B. Wakin

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/michael-b-wakin/

## Facts

| Field | Value |
| --- | --- |
| Citations | 27,395 |
| Field | Sparse and Compressive Sensing Techniques |
| h-index | 48 |
| i10-index | 113 |
| Last Known Institution | Colorado School of Mines |
| OpenAlex ID | https://openalex.org/A5065207980 |
| ORCID iD | https://orcid.org/0000-0002-2165-4586 |
| Works | 244 |

## Researcher papers

- [A Simple Proof of the Restricted Isometry Property for Random Matrices](https://scholariq.org/papers/a-simple-proof-of-the-restricted-isometry-property-for-random-matrices/)
- [Signal Processing With Compressive Measurements](https://scholariq.org/papers/signal-processing-with-compressive-measurements/)
- [Analysis of Orthogonal Matching Pursuit Using the Restricted Isometry Property](https://scholariq.org/papers/analysis-of-orthogonal-matching-pursuit-using-the-restricted-isometry-property/)
- [The smashed filter for compressive classification and target recognition](https://scholariq.org/papers/the-smashed-filter-for-compressive-classification-and-target-recognition/)

## Researcher topics

- [Sparse and Compressive Sensing Techniques](https://scholariq.org/topics/sparse-and-compressive-sensing-techniques/)
- [Microwave Imaging and Scattering Analysis](https://scholariq.org/topics/microwave-imaging-and-scattering-analysis/)
- [Image and Signal Denoising Methods](https://scholariq.org/topics/image-and-signal-denoising-methods/)
- [Blind Source Separation Techniques](https://scholariq.org/topics/blind-source-separation-techniques/)
- [Distributed Sensor Networks and Detection Algorithms](https://scholariq.org/topics/distributed-sensor-networks-and-detection-algorithms/)

## Researcher university

- [Colorado School of Mines](https://scholariq.org/institutions/colorado-school-of-mines/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.