C.D. McGillem

72 papers receiving 2.3k citations

Peers

C.D. McGillem
Comparison fields: 5 of 137
  • Statistical and Nonlinear Physics 363
  • Signal Processing 305
  • Computer Vision and Pattern Recognition 490
  • Computer Networks and Communications 447
  • Cognitive Neuroscience 353
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Countries citing papers authored by C.D. McGillem

Since Specialization
Citations

This map shows the geographic impact of C.D. McGillem'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 C.D. McGillem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C.D. McGillem more than expected).

Fields of papers citing papers by C.D. McGillem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C.D. McGillem. 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 C.D. McGillem. The network helps show where C.D. McGillem may publish in the future.

Co-authors

The 22 scholars most cited alongside C.D. McGillem, 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 C.D. McGillem Line = papers co-authored together C.D. McGillem links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994385
2 1989233
3 1995209
4 1988190
5
Continuous and discrete signal and system analysis
1974145
6
Probabilistic methods of signal and system analysis
1971123
7 200097
8 197788
9
Modern communications and spread spectrum
198576
10 198473
11
Signal processing in evoked potential research: averaging and modeling.
198172
12 198972
13 197869
14 200364
15 198448
16 199147
17 198542
18
Machine processing of remotely sensed data
197537
19
Signal processing in evoked potential research: applications of filtering and pattern recognition.
198136
20
Methods of signal and system analysis
196735

About C.D. McGillem

C.D. McGillem is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering and Control and Systems Engineering, having authored 75 papers that have together received 2.6k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (12 papers), Neural Networks and Applications (9 papers), Millimeter-Wave Propagation and Modeling (9 papers), Advanced MIMO Systems Optimization (8 papers), Power Line Communications and Noise (7 papers), Blind Source Separation Techniques (7 papers), Optical measurement and interference techniques (6 papers) and Fault Detection and Control Systems (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (363 citations), Signal Processing (305 citations), Computer Vision and Pattern Recognition (490 citations), Computer Networks and Communications (447 citations) and Cognitive Neuroscience (353 citations). C.D. McGillem has collaborated with scholars based in United States, Taiwan and Belgium. Frequent co-authors include Ghobad Heidari-Bateni, Theodore S. Rappaport, George R. Cooper, J.A. Roecker, Anne Smith, Lisa Goffman, Jorge I. Aunon, P. E. Anuta, Carlos Pomalaza‐Ráez and Howard N. Zelaznik. Their work appears in journals such as IEEE Transactions on Aerospace and Electronic Systems, IEEE Transactions on Biomedical Engineering, IEEE Transactions on Vehicular Technology, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Communications.

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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