F. Kanaya
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Computational Theory and Mathematics top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Co-authors
- Kenji NakagawaShojiro MiyakeTomohiko UyematsuJun MuramatsuTe Sun HanHiroshi YasudaH HashimotoEtienne Barnard
- Topics
- Algorithms and Data Compression (8 papers)Cellular Automata and Applications (8 papers)DNA and Biological Computing (5 papers)
- Cited by
- Computational Theory and MathematicsArtificial IntelligenceComputer Vision and Pattern Recognition
- Partner nations
- JapanSouth Africa
In The Last Decade
F. Kanaya
30 papers receiving 277 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 141
- Electrical and Electronic Engineering 112
- Computational Theory and Mathematics 74
- Computer Vision and Pattern Recognition 72
- Computer Networks and Communications 51
Countries citing papers authored by F. Kanaya
This map shows the geographic impact of F. Kanaya'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 F. Kanaya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites F. Kanaya more than expected).
Fields of papers citing papers by F. Kanaya
This network shows the impact of papers produced by F. Kanaya. 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 F. Kanaya. The network helps show where F. Kanaya may publish in the future.
Co-authorship network of co-authors of F. Kanaya
This figure shows the co-authorship network connecting the top 25 collaborators of F. Kanaya. A scholar is included among the top collaborators of F. Kanaya 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 F. Kanaya. F. Kanaya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Performance of Multistage Universal Decoder for Given Linear Codes over Additive Noise Channels | 1 |
| 2 | 0 | |
| 3 | 14 | |
| 4 | 1 | |
| 5 | An Almost Sure Recurrence Theorem with Distortion for Stationary Ergodic Sources | 2 |
| 6 | A Signal-to-Noise Enhancer with Extended Bandwidth Using Two MSSW Filters and Two 90 Hybrids | 3 |
| 7 | Coding Theorems on Correlated General Sources | 53 |
| 8 | 17 | |
| 9 | 9 | |
| 10 | 25 | |
| 11 | 5 | |
| 12 | Optimal decision tree design based on information theoretical cost bound | 3 |
| 13 | 41 | |
| 14 | 13 | |
| 15 | Bayes statistical behavior and valid generalization of pattern classifying neural networks | 4 |
| 16 | 16 | |
| 17 | 0 | |
| 18 | 4 | |
| 19 | 2 | |
| 20 | 21 |
About F. Kanaya
F. Kanaya is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Statistics and Probability, having authored 32 papers that have together received 292 indexed citations. Recurring topics across this work include Algorithms and Data Compression (8 papers), Cellular Automata and Applications (8 papers) and DNA and Biological Computing (5 papers). The work is most often cited by research in Computational Theory and Mathematics (74 citations), Artificial Intelligence (141 citations) and Computer Vision and Pattern Recognition (72 citations). F. Kanaya has collaborated with scholars based in Japan and South Africa. Frequent co-authors include Kenji Nakagawa, Shojiro Miyake, Tomohiko Uyematsu, Jun Muramatsu, Te Sun Han, Hiroshi Yasuda, H Hashimoto, Etienne Barnard, Yasuhiko Ishikawa and Toshio Nishikawa. Their work appears in journals such as IEEE Transactions on Information Theory, Optics Letters 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.