Michael Muma
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
- Blind Source Separation Techniques
- Direction-of-Arrival Estimation Techniques
- Statistics and Probability top 2%
- Advanced Statistical Methods and Models
Papers in
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- Bayesian Methods and Mixture Models 10
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- Advanced Statistical Methods and Models 12
- Statistical Methods and Inference 11
- Co-authors
- Abdelhak M. Zoubir (60 shared papers)Visa Koivunen (7 shared papers)Yacine Chakhchoukh (2 shared papers)Esa Ollila (6 shared papers)Daniel P. Palomar (8 shared papers)Mengling Feng (3 shared papers)V. Koivunen (1 shared paper)Cuntai Guan (1 shared paper)
In The Last Decade
Michael Muma
74 papers receiving 882 citations
Peers
Comparison fields: 5 of 90
- Signal Processing 239
- Statistics and Probability 167
- Statistics, Probability and Uncertainty 65
- Computational Mechanics 173
- Computational Mathematics 5
Countries citing papers authored by Michael Muma
This map shows the geographic impact of Michael Muma's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Muma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Muma more than expected).
Fields of papers citing papers by Michael Muma
This network shows the impact of papers produced by Michael Muma. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Muma. The network helps show where Michael Muma may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Muma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 291 | |
| 2 | 2018 | 50 | |
| 3 | 2012 | 50 | |
| 4 | 2015 | 47 | |
| 5 | 2017 | 32 | |
| 6 | 2012 | 24 | |
| 7 | 2017 | 24 | |
| 8 | 2017 | 23 | |
| 9 | 2017 | 22 | |
| 10 | 2012 | 21 | |
| 11 | 2018 | 20 | |
| 12 | 2015 | 17 | |
| 13 | 2013 | 14 | |
| 14 | 2015 | 11 | |
| 15 | 2016 | 11 | |
| 16 | 2015 | 11 | |
| 17 | 2019 | 10 | |
| 18 | 2017 | 9 | |
| 19 | 2020 | 9 | |
| 20 | 2019 | 9 |
About Michael Muma
Michael Muma is a scholar working on Artificial Intelligence, Statistics and Probability, Signal Processing, Computer Networks and Communications and Computational Mechanics, having authored 79 papers that have together received 912 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (12 papers), Statistical Methods and Inference (11 papers), Bayesian Methods and Mixture Models (10 papers), Energy Efficient Wireless Sensor Networks (9 papers), Speech and Audio Processing (9 papers), Sparse and Compressive Sensing Techniques (8 papers), Advanced Statistical Process Monitoring (8 papers) and Control Systems and Identification (7 papers). The work is most often cited by research in Signal Processing (239 citations), Statistics and Probability (167 citations), Statistics, Probability and Uncertainty (65 citations), Computational Mechanics (173 citations) and Computational Mathematics (5 citations). Michael Muma has collaborated with scholars based in Germany, Hong Kong and Finland. Frequent co-authors include Abdelhak M. Zoubir, Visa Koivunen, Yacine Chakhchoukh, Esa Ollila, Daniel P. Palomar, Mengling Feng, V. Koivunen, Cuntai Guan, Jorge Plata-Chaves and Martin Vetterli. Their work appears in journals such as IEEE Transactions on Signal Processing, Signal Processing, IEEE Transactions on Biomedical Engineering, IEEE Signal Processing Magazine and Frontiers in Psychology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.