J.C. Principe

1.2k citations
26 papers · 990 indexed · 1 hit paper · h-index 10
Topics
Neural Networks and Applications (9 papers)Blind Source Separation Techniques (7 papers)EEG and Brain-Computer Interfaces (7 papers)

In The Last Decade

J.C. Principe

26 papers receiving 963 citations

Hit Papers

Neural Networks (IJCNN), The 2011 International Joint Con...20112026201620212011100200300

Peers

J.C. Principe
Comparison fields: 5 of 115
  • Artificial Intelligence 321
  • Signal Processing 285
  • Computational Mechanics 229
  • Computer Vision and Pattern Recognition 174
  • Cognitive Neuroscience 174
Replace Temujin Gautama with:
Temujin Gautama Belgium
Miguel Lázaro-Gredilla Spain
Xiaoping Lai China
Naohiro Ishii Japan
Ahmad Ayatollahi Iran
Romis Attux Brazil
Kenneth E. Hild United States
Yoshinobu Kawahara Japan
Christin Schäfer Germany
Ana Maria Tomé Portugal
J.C. Principe relative to Temujin Gautama Belgium Temujin Gautama's profile →
Citations per field
00.5×4.2×
Temujin Gautama · 1×
Citations per year

Countries citing papers authored by J.C. Principe

Since Specialization
Citations

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

Fields of papers citing papers by J.C. Principe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J.C. Principe

This figure shows the co-authorship network connecting the top 25 collaborators of J.C. Principe. A scholar is included among the top collaborators of J.C. Principe based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with J.C. Principe. J.C. Principe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 35
2
Neural Networks (IJCNN), The 2011 International Joint Conference onbreakdown →
377
3 183
4 1
5 150
6 64
7 2
8 1
9
Information theoretic clustering: a unifying review of three recent algorithms
2
10 1
11 3
12 43
13 1
14 2
15 2
16 3
17
Spatio-temporal models in biological and artificial systems
33
18 12
19
Automatic recognition of spike and wave bursts.
9
20 9

About J.C. Principe

J.C. Principe is a scholar working on Signal Processing, Architecture and Cognitive Neuroscience, having authored 26 papers that have together received 990 indexed citations. Recurring topics across this work include Neural Networks and Applications (9 papers), Blind Source Separation Techniques (7 papers) and EEG and Brain-Computer Interfaces (7 papers). The work is most often cited by research in Signal Processing (285 citations), Computational Mechanics (229 citations) and Artificial Intelligence (321 citations). J.C. Principe has collaborated with scholars based in United States, South Korea and Portugal. Frequent co-authors include Reeju Pokharel, Sohan Seth, Il Memming Park, Weifeng Liu, Jianbo Gao, Jing Hu, Weifeng Liu, Puskal P. Pokharel, Yinping Cao and Lingyun Gu. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Biomedical Engineering and Physics Letters A.

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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