Daniel Ménard

21 papers receiving 240 citations

Peers

Daniel Ménard
Comparison fields: 5 of 39
  • Hardware and Architecture 36
  • Signal Processing 49
  • Computational Theory and Mathematics 63
  • Computer Networks and Communications 81
  • Biomedical Engineering 94
Replace V.A. Chouliaras with:
V.A. Chouliaras United Kingdom
Gene Frantz United States
Shushan Qiao China
John Grosspietsch United States
Vasileios Leon Greece
Fredrik Hekland Norway
Sandeep Kakde India
Daniel Chillet France
Tetsuya Fujie Japan
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Citations per year

Countries citing papers authored by Daniel Ménard

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Ménard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Daniel Ménard, 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 Daniel Ménard Line = papers co-authored together Daniel Ménard links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201271
2 200334
3 201623
4 200818
5 200617
6 200615
7 199614
8 202212
9 200211
10 20089
11 20048
12 19996
13 20064
14 20023
15 19962
16 20001
17
Noise model for Accuracy Constraint Determination in Fixed-Point Systems
20071
18 20061
19 20011
20 20061

About Daniel Ménard

Daniel Ménard is a scholar working on Computational Theory and Mathematics, Signal Processing, Hardware and Architecture, Computer Networks and Communications and Control and Systems Engineering, having authored 22 papers that have together received 254 indexed citations. Recurring topics across this work include Numerical Methods and Algorithms (8 papers), Digital Filter Design and Implementation (6 papers), Advanced Adaptive Filtering Techniques (4 papers), Embedded Systems Design Techniques (4 papers), Control Systems and Identification (4 papers), Energy Efficient Wireless Sensor Networks (3 papers), Parallel Computing and Optimization Techniques (3 papers) and Helicobacter pylori-related gastroenterology studies (3 papers). The work is most often cited by research in Hardware and Architecture (36 citations), Signal Processing (49 citations), Computational Theory and Mathematics (63 citations), Computer Networks and Communications (81 citations) and Biomedical Engineering (94 citations). Daniel Ménard has collaborated with scholars based in France, Canada and Belgium. Frequent co-authors include Olivier Sentieys, Muhammad Mahtab Alam, Olivier Berder, Éric Tremblay, Nicolas Hervé, Elyes Ben Hamida, Alberto Bosio, Pascal Scalart, Pierre Chailler and Mélissa Chénard. Their work appears in journals such as The Anatomical Record, IEEE Access, Frontiers in bioscience, Journal of Cellular Biochemistry and Microscopy Research and Technique.

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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