Davide Mattera

852 citations
60 papers · 629 · h-index 14

Impact in

Papers in

Davide Mattera

53 papers receiving 570 citations

Peers

Davide Mattera
Comparison fields: 5 of 76
  • Signal Processing 96
  • Computer Networks and Communications 188
  • Electrical and Electronic Engineering 341
  • Computer Vision and Pattern Recognition 76
  • Artificial Intelligence 115
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E. Zervas Greece
Roberto Cusani Italy
S. Golden United States
Nauman Shahid Pakistan
Xiao-Hu Yu China
Georgy Shevlyakov Russia
M. Zahidul H. Bhuiyan Finland
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Yao Liang United States
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Citations per field
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Citations per year

Countries citing papers authored by Davide Mattera

Since Specialization
Citations

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

Fields of papers citing papers by Davide Mattera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Davide Mattera, 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 Davide Mattera Line = papers co-authored together Davide Mattera links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998185
2 200531
3 201229
4 201527
5 200224
6 201522
7 201520
8 199920
9 201519
10 201219
11 200317
12 201416
13 200815
14 201914
15 199912
16 201512
17 201511
18 202011
19
Generalized support vector machines.
199910
20 202110

About Davide Mattera

Davide Mattera is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Signal Processing, Computational Mechanics and Control and Systems Engineering, having authored 60 papers that have together received 629 indexed citations. Recurring topics across this work include PAPR reduction in OFDM (28 papers), Wireless Communication Networks Research (24 papers), Advanced Wireless Communication Techniques (21 papers), Optical Network Technologies (10 papers), Blind Source Separation Techniques (8 papers), Advanced Power Amplifier Design (7 papers), Structural Health Monitoring Techniques (5 papers) and Advanced MIMO Systems Optimization (4 papers). The work is most often cited by research in Signal Processing (96 citations), Computer Networks and Communications (188 citations), Electrical and Electronic Engineering (341 citations), Computer Vision and Pattern Recognition (76 citations) and Artificial Intelligence (115 citations). Davide Mattera has collaborated with scholars based in Italy, France and Canada. Frequent co-authors include Simon Haykin, Mario Tanda, Maurice Bellanger, L. Paura, F. Palmieri, S. Haykin, Luigi Paura, Gianmarco Romano, Giacinto Gelli and Pierluigi Salvo Rossi. Their work appears in journals such as Signal Processing, IEEE Transactions on Signal Processing, Physical Communication, Neurocomputing and Digital Signal Processing.

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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