M. A. Navascués
- Mathematical Physics top 0.5%
- Statistical and Nonlinear Physics top 1%
- Computational Mechanics top 5%
- Applied Mathematics top 5%
- Economics and Econometrics top 5%
- Co-authors
- A. K. B. ChandMaría Victoria SebastiánP. ViswanathanMd. Nasim AkhtarM. G. PrasadSaurabh VermaR. N. MohapatraPeter Massopust
- Topics
- Mathematical Dynamics and Fractals (80 papers)Advanced Mathematical Theories and Applications (34 papers)advanced mathematical theories (20 papers)
- Journals
- Journal of Mathematical Analysis and ApplicationsChaos Solitons & FractalsJournal of Computational and Applied Mathematics
- Partner nations
- SpainIndiaUnited States
In The Last Decade
M. A. Navascués
95 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 73
- Mathematical Physics 1.2k
- Statistical and Nonlinear Physics 712
- Computational Mechanics 300
- Applied Mathematics 178
- Economics and Econometrics 167
Countries citing papers authored by M. A. Navascués
This map shows the geographic impact of M. A. Navascués'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 M. A. Navascués with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. A. Navascués more than expected).
Fields of papers citing papers by M. A. Navascués
This network shows the impact of papers produced by M. A. Navascués. 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 M. A. Navascués. The network helps show where M. A. Navascués may publish in the future.
Co-authorship network of co-authors of M. A. Navascués
This figure shows the co-authorship network connecting the top 25 collaborators of M. A. Navascués. A scholar is included among the top collaborators of M. A. Navascués 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 M. A. Navascués. M. A. Navascués is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 3 | |
| 7 | 9 | |
| 8 | 5 | |
| 9 | 2 | |
| 10 | 6 | |
| 11 | 17 | |
| 12 | Hidden variable A-fractal functions and their monotonicity aspects | 3 |
| 13 | 26 | |
| 14 | 58 | |
| 15 | 9 | |
| 16 | Generalized hermite fractal interpolation | 20 |
| 17 | 166 | |
| 18 | Fractal trigonometric approximation. | 32 |
| 19 | 7 | |
| 20 | 75 |
About M. A. Navascués
M. A. Navascués is a scholar working on Mathematical Physics, Statistical and Nonlinear Physics and Applied Mathematics, having authored 100 papers that have together received 1.4k indexed citations. Recurring topics across this work include Mathematical Dynamics and Fractals (80 papers), Advanced Mathematical Theories and Applications (34 papers) and advanced mathematical theories (20 papers). The work is most often cited by research in Mathematical Physics (1.2k citations), Statistical and Nonlinear Physics (712 citations) and Modeling and Simulation (81 citations). M. A. Navascués has collaborated with scholars based in Spain, India and United States. Frequent co-authors include A. K. B. Chand, María Victoria Sebastián, P. Viswanathan, Md. Nasim Akhtar, M. G. Prasad, Saurabh Verma, R. N. Mohapatra, Peter Massopust, Vasileios Drakopoulos and F. G. Badía. Their work appears in journals such as Journal of Mathematical Analysis and Applications, Chaos Solitons & Fractals and Journal of Computational and Applied Mathematics.
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.