Michael Muma

1.3k citations
73 papers · 865 · h-index 12

Impact in

Papers in

Michael Muma

69 papers receiving 826 citations

Peers

Michael Muma
Comparison fields: 5 of 92
  • Signal Processing 222
  • Statistics and Probability 158
  • Statistics, Probability and Uncertainty 65
  • Computational Mathematics 5
  • Computational Mechanics 163
Replace Branko Kovačević with:
Branko Kovačević Serbia
Maciej Niedźwiecki Poland
P. Heinonen Finland
Yang Song Singapore
S. de Waele Netherlands
Hao He United States
A. Dogandzic United States
Tuncer C. Aysal United States
Daniele Angelosante Italy
Michael Muma relative to Branko Kovačević Serbia Branko Kovačević's profile →
Citations per field
00.5×4.3×
Branko Kovačević · 1×
Citations per year

Countries citing papers authored by Michael Muma

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Michael Muma Line = papers co-authored together Michael Muma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012278
2 201850
3 201248
4 201547
5 201730
6 201223
7 201722
8 201722
9 201722
10 201221
11 201820
12 201517
13 201511
14 201310
15 20179
16 20199
17 20199
18 20209
19 20248
20 20228

About Michael Muma

Michael Muma is a scholar working on Artificial Intelligence, Statistics and Probability, Signal Processing, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 73 papers that have together received 865 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (10 papers), Statistical Methods and Inference (10 papers), Bayesian Methods and Mixture Models (9 papers), Energy Efficient Wireless Sensor Networks (9 papers), Advanced Statistical Process Monitoring (8 papers), Sparse and Compressive Sensing Techniques (7 papers), Speech and Audio Processing (7 papers) and Distributed Sensor Networks and Detection Algorithms (6 papers). The work is most often cited by research in Signal Processing (222 citations), Statistics and Probability (158 citations), Statistics, Probability and Uncertainty (65 citations), Computational Mathematics (5 citations) and Computational Mechanics (163 citations). Michael Muma has collaborated with scholars based in Germany, Hong Kong and United States. Frequent co-authors include Abdelhak M. Zoubir, Visa Koivunen, Yacine Chakhchoukh, Esa Ollila, Daniel P. Palomar, V. Koivunen, Mengling Feng, Florian Roemer, Jorge Plata-Chaves and Cuntai Guan. Their work appears in journals such as IEEE Transactions on Signal Processing, Signal Processing, IEEE Signal Processing Magazine, IEEE Transactions on Biomedical Engineering 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.

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