Jun Muramatsu

66 papers receiving 670 citations

Peers

Jun Muramatsu
Comparison fields: 5 of 48
  • Acoustics and Ultrasonics 21
  • Statistical and Nonlinear Physics 196
  • Computer Networks and Communications 329
  • Computer Vision and Pattern Recognition 206
  • Electrical and Electronic Engineering 369
Replace Evangelos Pikasis with:
Evangelos Pikasis Greece
Jonathan N. Blakely United States
Jianhong Xiang China
Elad Cohen Israel
Masanobu Inubushi Japan
Xiaowen Li China
A. S. Dmitriev Russia
Anke Zhao China
Jean Barbier Italy
Kazutaka Kanno Japan
Jun Muramatsu relative to Evangelos Pikasis Greece Evangelos Pikasis's profile →
Citations per field
00.5×1.5×1.8×
Evangelos Pikasis · 1×
Citations per year

Countries citing papers authored by Jun Muramatsu

Since Specialization
Citations

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

Fields of papers citing papers by Jun Muramatsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Muramatsu, 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 Jun Muramatsu Line = papers co-authored together Jun Muramatsu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012131
2 200770
3 201366
4 200554
5 201232
6 201425
7 201022
8 200321
9 201221
10 201517
11 200715
12 200814
13 201013
14 201213
15 200312
16 200612
17 201112
18 200310
19 20069
20 20038

About Jun Muramatsu

Jun Muramatsu is a scholar working on Computer Networks and Communications, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence, having authored 67 papers that have together received 718 indexed citations. Recurring topics across this work include Wireless Communication Security Techniques (21 papers), Cellular Automata and Applications (18 papers), Error Correcting Code Techniques (17 papers), Chaos-based Image/Signal Encryption (14 papers), DNA and Biological Computing (14 papers), Cooperative Communication and Network Coding (13 papers), Underwater Vehicles and Communication Systems (8 papers) and Nonlinear Dynamics and Pattern Formation (7 papers). The work is most often cited by research in Acoustics and Ultrasonics (21 citations), Statistical and Nonlinear Physics (196 citations), Computer Networks and Communications (329 citations), Computer Vision and Pattern Recognition (206 citations) and Electrical and Electronic Engineering (369 citations). Jun Muramatsu has collaborated with scholars based in Japan, United States and Brazil. Frequent co-authors include Kazuyuki Yoshimura, Peter T. Davis, Atsushi Uchida, Hiroki Aida, Takahisa Harayama, Haruka Okumura, Tomohiko Uyematsu, Tadashi Wadayama, K. Asakawa and Fumio Kanaya. Their work appears in journals such as IEEE Transactions on Information Theory, Optics Express, Physical Review Letters, Scientific Reports and IEEE Photonics Technology Letters.

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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