Javier Vía

2.2k citations
109 papers · 1.7k · h-index 20

Impact in

Papers in

Javier Vía

106 papers receiving 1.6k citations

Peers

Javier Vía
Comparison fields: 5 of 90
  • Signal Processing 757
  • Computational Mathematics 14
  • Computer Networks and Communications 499
  • Computational Mechanics 384
  • Aerospace Engineering 334
Replace Roberto López-Valcarce with:
Roberto López-Valcarce Spain
George N. Karystinos Greece
V. Koivunen Finland
E.F. Deprettere Netherlands
Ali Pezeshki United States
Saeed Gazor Canada
Jisheng Dai China
Fuliang Yin China
Chad M. Spooner United States
Javier Vía relative to Roberto López-Valcarce Spain Roberto López-Valcarce's profile →
Citations per field
00.5×1.5×
Roberto López-Valcarce · 1×
Citations per year

Countries citing papers authored by Javier Vía

Since Specialization
Citations

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

Fields of papers citing papers by Javier Vía

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Javier Vía, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Javier Vía Line = papers co-authored together Javier Vía links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 109 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011145
2 2006126
3 2010117
4 200690
5 201085
6 201075
7 200759
8 201157
9 201339
10 200738
11 200532
12 200632
13 200831
14 201729
15 201027
16 201527
17 200724
18 201024
19 200822
20 200821

About Javier Vía

Javier Vía is a scholar working on Signal Processing, Computer Networks and Communications, Electrical and Electronic Engineering, Computational Mechanics and Artificial Intelligence, having authored 109 papers that have together received 1.7k indexed citations. Recurring topics across this work include Blind Source Separation Techniques (66 papers), Advanced Wireless Communication Techniques (24 papers), Distributed Sensor Networks and Detection Algorithms (24 papers), Advanced MIMO Systems Optimization (23 papers), Advanced Adaptive Filtering Techniques (14 papers), Neural Networks and Applications (14 papers), Cognitive Radio Networks and Spectrum Sensing (14 papers) and Wireless Communication Networks Research (12 papers). The work is most often cited by research in Signal Processing (757 citations), Computational Mathematics (14 citations), Computer Networks and Communications (499 citations), Computational Mechanics (384 citations) and Aerospace Engineering (334 citations). Javier Vía has collaborated with scholars based in Spain, United States and Germany. Frequent co-authors include Ignacio Santamarı́a, David Ramírez, Steven Van Vaerenbergh, J. Pérez, Louis L. Scharf, Luis Vielva, Roberto López-Valcarce, Gonzalo Vazquez-Vilar, Daniel P. Palomar and V́ıctor Elvira. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Transactions on Information Theory, Signal Processing, EURASIP Journal on Wireless Communications and Networking and IEEE Transactions on Vehicular Technology.

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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