Yoshihiro Okamoto

815 total citations
100 papers, 580 citations indexed

About

Yoshihiro Okamoto is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Yoshihiro Okamoto has authored 100 papers receiving a total of 580 indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Computational Theory and Mathematics, 54 papers in Computer Networks and Communications and 46 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Yoshihiro Okamoto's work include Cellular Automata and Applications (62 papers), Magnetic properties of thin films (41 papers) and Advanced Data Storage Technologies (36 papers). Yoshihiro Okamoto is often cited by papers focused on Cellular Automata and Applications (62 papers), Magnetic properties of thin films (41 papers) and Advanced Data Storage Technologies (36 papers). Yoshihiro Okamoto collaborates with scholars based in Japan, United States and Thailand. Yoshihiro Okamoto's co-authors include Hisashi Osawa, Y. Nakamura, H. Muraoka, Yasushi Kanai, Masato Yamashita, Hidetoshi Saito, K. Miura, Shozo Komaki, Simon John Greaves and Yoshio Suzuki and has published in prestigious journals such as Journal of Applied Physics, IEEE Transactions on Communications and Japanese Journal of Applied Physics.

In The Last Decade

Yoshihiro Okamoto

84 papers receiving 553 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yoshihiro Okamoto Japan 13 367 334 252 159 113 100 580
Hisashi Osawa Japan 12 333 0.9× 280 0.8× 205 0.8× 128 0.8× 111 1.0× 90 505
Roy D. Cideciyan Switzerland 13 196 0.5× 292 0.9× 99 0.4× 342 2.2× 171 1.5× 37 584
T.D. Howell United States 10 164 0.4× 130 0.4× 150 0.6× 168 1.1× 111 1.0× 25 445
Piya Kovintavewat Thailand 10 237 0.6× 220 0.7× 189 0.8× 92 0.6× 116 1.0× 79 403
Rick Galbraith United States 11 175 0.5× 230 0.7× 96 0.4× 193 1.2× 120 1.1× 33 379
E. Kurtas United States 15 294 0.8× 520 1.6× 87 0.3× 446 2.8× 184 1.6× 69 700
R.S. Indeck United States 11 58 0.2× 123 0.4× 147 0.6× 96 0.6× 99 0.9× 43 384
H.K. Thapar United States 14 303 0.8× 359 1.1× 115 0.5× 463 2.9× 292 2.6× 40 732
Jonathan D. Coker United States 10 118 0.3× 177 0.5× 73 0.3× 153 1.0× 80 0.7× 22 325
D. Palmer United States 8 71 0.2× 50 0.1× 179 0.7× 142 0.9× 53 0.5× 28 346

Countries citing papers authored by Yoshihiro Okamoto

Since Specialization
Citations

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

Fields of papers citing papers by Yoshihiro Okamoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoshihiro Okamoto

This figure shows the co-authorship network connecting the top 25 collaborators of Yoshihiro Okamoto. A scholar is included among the top collaborators of Yoshihiro Okamoto 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 Yoshihiro Okamoto. Yoshihiro Okamoto 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
1.
Nakamura, Y., et al.. (2025). A study on applying GA for performance improvement of SP decoder in SMR. AIP Advances. 15(3).
2.
Nakamura, Y., et al.. (2024). Improvement of SP Decoding Considering the Influence of Recording Patterns by Neural Network in SMR. IEEE Transactions on Magnetics. 60(9). 1–5.
3.
Nakamura, Y., et al.. (2023). A Study on Accelerating SP decoding by Neural Network in SMR System. j86 c. 1–2.
4.
Nakamura, Y., et al.. (2023). A Study on Accelerating SP Decoding by Neural Network in SMR System. IEEE Transactions on Magnetics. 59(11). 1–5. 1 indexed citations
5.
Nakamura, Y., et al.. (2022). A Study of Three-Dimensional Equalization for Reproducing a Double-Layer Magnetic Recording Medium. IEEE Transactions on Magnetics. 58(8). 1–4. 5 indexed citations
6.
Nakamura, Y., et al.. (2022). Performance Evaluation of Burst Error Correction by LDPC Coding and Iterative Decoding System in Magnetic Tape Drive. IEEE Transactions on Magnetics. 59(3). 1–5.
7.
Nakamura, Y., et al.. (2021). A Study on Performance Evaluation With Neural Network Detector in SMR System. IEEE Transactions on Magnetics. 58(4). 1–5.
8.
Nakamura, Y., et al.. (2021). A Study of Channel Time-Domain Response on Equalization for Reproducing a Double-Layer Magnetic Recording Medium. IEEE Transactions on Magnetics. 58(4). 1–5. 6 indexed citations
9.
Nakamura, Y., et al.. (2020). A Study on Neural Network Detector in SMR System. IEEE Transactions on Magnetics. 57(3). 1–5. 4 indexed citations
10.
Nakamura, Y., et al.. (2020). Improvement of Iterative Decoding With LLR Modulator by Neural Network Using Magnetic Transition Information in SMR System. IEEE Transactions on Magnetics. 57(2). 1–5. 10 indexed citations
11.
Nakamura, Y., et al.. (2020). A Study on AM–FM Combined Detection for Magnetic Recording Using STO Reading. IEEE Transactions on Magnetics. 57(2). 1–5. 3 indexed citations
12.
Nakamura, Y., et al.. (2020). Performance Improvement of Dual STO Reading With AM–FM Combined Detection for 3-D Magnetic Recording. IEEE Transactions on Magnetics. 57(3). 1–5. 4 indexed citations
13.
Nakamura, Y., Masaharu Nishimura, Yoshihiro Okamoto, et al.. (2008). Iterative decoding algorithm using attenuated information in PMR with bit-patterned medium. Journal of Magnetism and Magnetic Materials. 320(22). 3132–3135. 7 indexed citations
14.
Nakamura, Y., et al.. (2007). Performance Evaluation of LDPC Coding and Iterative Decoding System Using Burst Information. 90(5). 437–446. 1 indexed citations
15.
Okamoto, Yoshihiro, et al.. (2006). SAFETY DRIVING SUPPORT SYSTEM USING RFID. 5 indexed citations
16.
Nakamura, Y., et al.. (2004). A Study of Interactive Processing Between PRML Detection and Erasure Error Correction in Perpendicular Recording. IEEE Transactions on Magnetics. 40(4). 3105–3107. 1 indexed citations
17.
Saito, Hidetoshi, et al.. (1998). Error Rate Performance of Trellis Coded PR4ML System for Digital Magnetic Recording Channel with Partial Erasure. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 81(10). 2159–2165. 1 indexed citations
18.
Osawa, Hisashi, et al.. (1997). Neural Network Equalization of Nonlinear Channel with Partial Erasure. Journal of the Magnetics Society of Japan. 21(S_1_PMRS_96). S1_78–82.
19.
Osawa, Hisashi, et al.. (1996). Performance Improvement of PRML System for (1,7) RLL Code. IEICE Transactions on Electronics. 79(10). 1455–1460. 4 indexed citations
20.
Osawa, Hisashi, et al.. (1996). Performance of PRML systems in perpendicular magnetic recording by a bi-layered main-pole head. Journal of Magnetism and Magnetic Materials. 157-158. 262–263. 1 indexed citations

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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