Sparse and Compressive Sensing Techniques
Sparse and Compressive Sensing Techniques is a research topic within Computational Mechanics. Science Explorer counts 27k research works in it since 1959. 23.7% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the theory and applications of compressed sensing, including sparse representation, signal recovery, convex optimization, matrix completion, dictionary learning, orthogonal matching pursuit, robust reconstruction, and sparsity in signal processing.
- Compressed Sensing
- Sparse Representation
- Signal Recovery
- Convex Optimization
- Matrix Completion
- Sparse Approximation
- Dictionary Learning
- Orthogonal Matching Pursuit
- Robust Reconstruction
- Sparsity in Signal Processing
- Research works
- 27k fractional, since 1959
- In the world top 10%
- 6.5k per year above
- Top-10% rate
- 23.7% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- 0% the tick is no change
Which countries lead Sparse and Compressive Sensing Techniques research?
By volume, China and the United States publish the most (2.5k and 741 works in 2022–2025).
By volume, 2022–2025
- 1 China 2.5k works
- 2 United States 741 works
- 3 India 213 works
- 4 France 173 works
- 5 Germany 143 works
- 6 Japan 136 works
- 7 United Kingdom 129 works
- 8 Italy 95 works
- 9 Hong Kong 88 works
- 10 Canada 74 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Sparse and Compressive Sensing Techniques research?
By volume in 2022–2025, University of Electronic Science and Technology of China publishes the most Sparse and Compressive Sensing Techniques research, followed by Xidian University and National University of Defense Technology.
By volume, 2022–2025
- 1 University of Electronic Science and Technology of ChinaChina 98 works
- 2 Xidian UniversityChina 68 works
- 3 National University of Defense TechnologyChina 50 works
- 4 Harbin Institute of TechnologyChina 47 works
- 5 Beijing Institute of TechnologyChina 44 works
- 6 Zhejiang UniversityChina 38 works
- 7 Chinese Academy of SciencesChina 35 works
- 8 Beijing University of Posts and TelecommunicationsChina 32 works
- 9 Northwestern Polytechnical UniversityChina 32 works
- 10 Tsinghua UniversityChina 32 works
Who are the leading researchers in Sparse and Compressive Sensing Techniques?
The most-cited researchers publishing on Sparse and Compressive Sensing Techniques include Jerome H. Friedman, Wei Liu and H. Vincent Poor.
- 1 Jerome H. Friedman United States 11k citations
- 2 Wei Liu China 9.7k citations
- 3 H. Vincent Poor United States 9.5k citations
- 4 Stanley Osher United States 8k citations
- 5 Thomas S. Huang United States 7.4k citations
- 6 Robert W. Heath United States 7.1k citations
- 7 Trevor Darrell United States 6.7k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Sparse and Compressive Sensing Techniques research done?
The largest centres of Sparse and Compressive Sensing Techniques research in 2022–2025 are Beijing (China), Xi'an (China), Nanjing (China) and Shanghai (China). Among places with at least 20 works in it, it is an unusually large share of all research in Guilin and Shenzhen.
Largest cities, 2022–2025
Where it is the local speciality
- GuilinCN · 26.0 works6.2×
- ShenzhenCN · 91.9 works5.3×
Location quotient: how much more of its research is in Sparse and Compressive Sensing Techniques than the world average.
Where is the best place to study Sparse and Compressive Sensing Techniques?
Among universities, judged by research, Xidian University, University of Electronic Science and Technology of China and Southwest University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Xidian UniversityChina | 77.8 | 32.0% | 18.4× | 68 | +30.9% |
| 2 | University of Electronic Science and Technology of ChinaChina | 73.7 | 19.0% | 17.2× | 98 | +106.5% |
| 3 | Southwest UniversityChina | 68.9 | 21.0% | 9.4× | 26 | +343.8% |
| 4 | National University of Defense TechnologyChina | 68.4 | 25.4% | 12.8× | 50 | +42.1% |
| 5 | Northwestern Polytechnical UniversityChina | 63.5 | 31.4% | 5.5× | 32 | +104.7% |
| 6 | Beijing Institute of TechnologyChina | 61.9 | 18.0% | 7.3× | 44 | +164.9% |
| 7 | City University of Hong KongHong Kong | 61.5 | 25.1% | 6.0× | 18 | +87.1% |
| 8 | Aerospace Information Research InstituteChina | 61.3 | 27.9% | 18.4× | 11 | — |
| 9 | Harbin Institute of TechnologyChina | 58.3 | 24.2% | 5.6× | 47 | +79.8% |
| 10 | Hong Kong University of Science and TechnologyHong Kong | 57.6 | 30.3% | 5.8× | 11 | +31.3% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Sparse and Compressive Sensing Techniques research growing?
Output in 2018–2022 was 0% lower than in 2013–2017, peaking in 2018. The fastest-growing topics are Sparse and Compressive Sensing Techniques.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.