José M. Amigó
- Statistical and Nonlinear Physics top 0.5%
- Chaos control and synchronization 34
- Ceramics and Composites top 5%
- Economics and Econometrics top 1%
- Complex Systems and Time Series Analysis 24
- Signal Processing top 5%
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- Chaos-based Image/Signal Encryption 14
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- Mathematical Dynamics and Fractals 21
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- Neural Networks and Applications 19
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- X-ray Diffraction in Crystallography 16
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- Cellular Automata and Applications 14
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- Neural dynamics and brain function 14
José M. Amigó
149 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Statistical and Nonlinear Physics 975
- Ceramics and Composites 223
- Economics and Econometrics 706
- Signal Processing 242
- Computer Vision and Pattern Recognition 452
Countries citing papers authored by José M. Amigó
This map shows the geographic impact of José M. Amigó'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 José M. Amigó with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites José M. Amigó more than expected).
Fields of papers citing papers by José M. Amigó
This network shows the impact of papers produced by José M. Amigó. 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 José M. Amigó. The network helps show where José M. Amigó may publish in the future.
Co-authorship network
The 25 scholars most cited alongside José M. Amigó, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 10 | |
| 5 | 2022 | 4 | |
| 6 | 2016 | 25 | |
| 7 | 2016 | 1 | |
| 8 | 2016 | 2 | |
| 9 | 2014 | 1 | |
| 10 | 2013 | 1 | |
| 11 | 2012 | 12 | |
| 12 | 2011 | 14 | |
| 13 | 2009 | 35 | |
| 14 | 2005 | 14 | |
| 15 | Representing 2D Objects. Comparison of Several Self-Organizing Networks | 2002 | 2 |
| 16 | 1987 | 4 | |
| 17 | Beryl: Structural refinement of a sodium-rich natural crystal from Lassur mine (Ariège, France) | 1984 | 1 |
| 18 | Cation distribution and local crystal chemistries of calcium-containing pyroxenes | 1984 | 1 |
| 19 | Fe-Mg M1 site distribution in some clinopyroxenes from Santa Olalla (Huelva, Spain) | 1981 | 1 |
| 20 | Fe-dolomite (teruelite) from the Keuper of the southern sector of the Iberian Mountain Range, Spain | 1981 | 2 |
About José M. Amigó
José M. Amigó is a scholar working on Statistical and Nonlinear Physics, Mathematical Physics and Ceramics and Composites, having authored 157 papers that have together received 3.1k indexed citations. Recurring topics across this work include Chaos control and synchronization (34 papers), Complex Systems and Time Series Analysis (24 papers), Mathematical Dynamics and Fractals (21 papers), Neural Networks and Applications (19 papers), X-ray Diffraction in Crystallography (16 papers), Cellular Automata and Applications (14 papers), Neural dynamics and brain function (14 papers) and Chaos-based Image/Signal Encryption (14 papers). The work is most often cited by research in Statistical and Nonlinear Physics (975 citations), Ceramics and Composites (223 citations) and Economics and Econometrics (706 citations). José M. Amigó has collaborated with scholars based in Spain, Poland and Germany. Frequent co-authors include Janusz Szczepański, Ljupčo Kocarev, Miguel A. F. Sanjuán, Samuel Zambrano, María V. Sánchez-Vives, Matthew B. Kennel, F. J. Serrano, Ángel Giménez, J. Bastida and Karsten Keller. Their work appears in journals such as PLoS ONE, Journal of the American Ceramic Society and Atmospheric Environment.
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.