Gema Piñero

1.1k citations
72 papers · 791 indexed · h-index 16
Topics
Speech and Audio Processing (38 papers)Advanced Adaptive Filtering Techniques (33 papers)Acoustic Wave Phenomena Research (22 papers)

In The Last Decade

Gema Piñero

65 papers receiving 771 citations

Peers

Gema Piñero
Comparison fields: 5 of 51
  • Computational Mechanics 554
  • Signal Processing 489
  • Biomedical Engineering 286
  • Automotive Engineering 138
  • Electrical and Electronic Engineering 99
Replace María de Diego with:
María de Diego Spain
Miguel Ferrer Spain
Yoshinobu Kajikawa Japan
IM STOTHERS United Kingdom
S.M. Kuo United States
Dongyuan Shi Singapore
Wolfgang Klippel Germany
L. J. Eriksson United States
Jinwei Sun China
Yusuke Hioka Japan
Gema Piñero relative to María de Diego Spain María de Diego's profile →
Citations per field
00.5×1.5×
María de Diego · 1×
Citations per year

Countries citing papers authored by Gema Piñero

Since Specialization
Citations

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

Fields of papers citing papers by Gema Piñero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gema Piñero

This figure shows the co-authorship network connecting the top 25 collaborators of Gema Piñero. A scholar is included among the top collaborators of Gema Piñero 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 Gema Piñero. Gema Piñero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 11
3 20
4 22
5 2
6 5
7 96
8
Efficient GPU implementation of Lattice-Reduction-Aided Multiuser Precoding
2
9
Application of Multi-core and GPU Architectures on Signal Processing: Case Studies
0
10 1
11 20
12 15
13 4
14 10
15
Efficient Error Vector Calculation in Affine Projection Algorithms for Active Noise Control
3
16 8
17 1
18
Simultaneous Measurement of Multichannel Acoustic Systems
4
19 26
20
SUBJECTIVE EVAULATION OF ACTIVE NOISE CONTROL TECHNIQUES APPLIED TO ENGINE NOISE
1

About Gema Piñero

Gema Piñero is a scholar working on Signal Processing, Computational Mechanics and Developmental Biology, having authored 72 papers that have together received 791 indexed citations. Recurring topics across this work include Speech and Audio Processing (38 papers), Advanced Adaptive Filtering Techniques (33 papers) and Acoustic Wave Phenomena Research (22 papers). The work is most often cited by research in Signal Processing (489 citations), Computational Mechanics (554 citations) and Automotive Engineering (138 citations). Gema Piñero has collaborated with scholars based in Spain, United Kingdom and Hungary. Frequent co-authors include Alberto González, María de Diego, Miguel Ferrer, J. García-Bonito, Carmen Botella, Luis Vergara, Alberto Broatch, J.M. Desantes, Narcís Cardona and Jordan Cheer. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Signal Processing and The Journal of the Acoustical Society of America.

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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