Javier Garrigós
- Electrical and Electronic Engineering
- Pollution top 10%
- Industrial and Manufacturing Engineering
- Ocean Engineering
- Cognitive Neuroscience
- Co-authors
- José Carlos García‐GómezJosé Manuel FerrándezJuan HinojosaF. Javier ToledoEduardo FernándezCristina Soto‐SánchezGinés Doménech‐AsensiIsidro Villó-Pérez
- Topics
- Advanced Memory and Neural Computing (5 papers)Neural Networks Stability and Synchronization (5 papers)CCD and CMOS Imaging Sensors (4 papers)
In The Last Decade
Javier Garrigós
20 papers receiving 235 citations
Peers
Comparison fields: 5 of 58
- Electrical and Electronic Engineering 86
- Pollution 79
- Industrial and Manufacturing Engineering 38
- Ocean Engineering 27
- Cognitive Neuroscience 27
Countries citing papers authored by Javier Garrigós
This map shows the geographic impact of Javier Garrigós'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 Javier Garrigós with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Javier Garrigós more than expected).
Fields of papers citing papers by Javier Garrigós
This network shows the impact of papers produced by Javier Garrigós. 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 Javier Garrigós. The network helps show where Javier Garrigós may publish in the future.
Co-authorship network of co-authors of Javier Garrigós
This figure shows the co-authorship network connecting the top 25 collaborators of Javier Garrigós. A scholar is included among the top collaborators of Javier Garrigós 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 Javier Garrigós. Javier Garrigós 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 | 4 | |
| 3 | 93 | |
| 4 | 35 | |
| 5 | 7 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | Implementing large-kernel 2-D filters using Impulse CoDeveloper | 1 |
| 11 | 19 | |
| 12 | 17 | |
| 13 | 3 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 27 | |
| 19 | 1 | |
| 20 | 15 |
About Javier Garrigós
Javier Garrigós is a scholar working on Hardware and Architecture, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 21 papers that have together received 241 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (5 papers), Neural Networks Stability and Synchronization (5 papers) and CCD and CMOS Imaging Sensors (4 papers). The work is most often cited by research in Pollution (79 citations), Industrial and Manufacturing Engineering (38 citations) and Ocean Engineering (27 citations). Javier Garrigós has collaborated with scholars based in Spain and Argentina. Frequent co-authors include José Carlos García‐Gómez, José Manuel Ferrández, Juan Hinojosa, F. Javier Toledo, Eduardo Fernández, Cristina Soto‐Sánchez, Ginés Doménech‐Asensi, Isidro Villó-Pérez, C Colodro-Conde and R. Toledo-Moreo. Their work appears in journals such as IEEE Transactions on Microwave Theory and Techniques, Neurocomputing and Agricultural Water Management.
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.