M. Larimore

3.6k citations
40 papers · 1.8k indexed · 1 hit paper · h-index 13

M. Larimore

32 papers receiving 1.6k citations

Hit Papers

Stationary and nonstationary learning characteristics of ...1.0k19762026199220092505007501000

Peers

M. Larimore
Comparison fields: 5 of 71
  • Signal Processing 1.2k
  • Computational Mechanics 1.2k
  • Computer Vision and Pattern Recognition 260
  • Control and Systems Engineering 220
  • Artificial Intelligence 242
Replace J.J. Shynk with:
J.J. Shynk United States
J Treichler United States
Azzedine Zerguine Saudi Arabia
Ian K. Proudler United Kingdom
J.-J. Fuchs France
Miloš Doroslovački United States
Wasfy B. Mikhael United States
T. Aboulnasr Canada
E.F. Deprettere Netherlands
Giovanni L. Sicuranza Italy
M. Larimore relative to J.J. Shynk United States J.J. Shynk's profile →
Citations per field
00.5×1.5×
J.J. Shynk · 1×
Citations per year

Countries citing papers authored by M. Larimore

Since Specialization
Citations

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

Fields of papers citing papers by M. Larimore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Larimore. 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 M. Larimore. The network helps show where M. Larimore may publish in the future.

Co-authorship network

The 14 scholars most cited alongside M. Larimore, 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 M. Larimore Line = papers co-authored together M. Larimore links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20061
2 20051
3 200523
4 20052
5 20051
6 20051
7 20050
8 20056
9 20050
10 20031
11 20027
12 20022
13 200133
14 19920
15 198560
16 198215
17 198012
18 197823
19 19784
20 19779

About M. Larimore

M. Larimore is a scholar working on Signal Processing, Computational Mechanics and Computer Vision and Pattern Recognition, having authored 40 papers that have together received 1.8k indexed citations. Recurring topics across this work include Advanced Adaptive Filtering Techniques (30 papers), Blind Source Separation Techniques (24 papers), Speech and Audio Processing (13 papers), Image and Signal Denoising Methods (10 papers), Neural Networks and Applications (5 papers), Digital Filter Design and Implementation (3 papers), Advanced Wireless Communication Techniques (3 papers) and Sparse and Compressive Sensing Techniques (2 papers). The work is most often cited by research in Signal Processing (1.2k citations), Computational Mechanics (1.2k citations) and Computer Vision and Pattern Recognition (260 citations). M. Larimore has collaborated with scholars based in United States, Australia and France. Frequent co-authors include C.R. Johnson, Bernard Widrow, J. McCool, J Treichler, N.J. Bershad, P. Feintuch, Brian D. O. Anderson, Inbar Fijalkow, N. Ahmed and Juan M. Martín‐Sánchez. Their work appears in journals such as Proceedings of the IEEE, IEEE Transactions on Magnetics, IEEE Transactions on Signal Processing, IEEE Transactions on Circuits and Systems and International Conference on Acoustics, Speech, and Signal Processing.

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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