Dan Lascu

599 citations
74 papers · 359 · h-index 9

Impact in

Papers in

Dan Lascu

66 papers receiving 330 citations

Peers

Dan Lascu
Comparison fields: 5 of 52
  • Neurology 87
  • Mathematical Physics 38
  • Automotive Engineering 47
  • Computer Vision and Pattern Recognition 75
  • Electrical and Electronic Engineering 178
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Jiayan Jiang China
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Citations per field
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Citations per year

Countries citing papers authored by Dan Lascu

Since Specialization
Citations

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

Fields of papers citing papers by Dan Lascu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Dan Lascu, 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 Dan Lascu Line = papers co-authored together Dan Lascu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019100
2 200518
3 201716
4 201916
5 201415
6
LabVIEW based biomedical signal acquisition and processing
200711
7 20179
8 20098
9 20138
10 20178
11 20177
12 20217
13 20156
14 20066
15
Modeling, simulation and design of input filter for matrix converters
20056
16
LabVIEW event detection using Pan-Tompkins algorithm
20075
17 20205
18
DC Motor Drive with PFC Rectifier
20084
19
Electrocardiogram compression and optimal ECG filtering algorithms
20084
20 20144

About Dan Lascu

Dan Lascu is a scholar working on Electrical and Electronic Engineering, Mathematical Physics, Control and Systems Engineering, Applied Mathematics and Automotive Engineering, having authored 74 papers that have together received 359 indexed citations. Recurring topics across this work include Advanced DC-DC Converters (46 papers), Multilevel Inverters and Converters (35 papers), Silicon Carbide Semiconductor Technologies (20 papers), Mathematical Dynamics and Fractals (13 papers), Microgrid Control and Optimization (8 papers), Advanced Battery Technologies Research (7 papers), Analog and Mixed-Signal Circuit Design (6 papers) and Photovoltaic System Optimization Techniques (5 papers). The work is most often cited by research in Neurology (87 citations), Mathematical Physics (38 citations), Automotive Engineering (47 citations), Computer Vision and Pattern Recognition (75 citations) and Electrical and Electronic Engineering (178 citations). Dan Lascu has collaborated with scholars based in Romania, Germany and United States. Frequent co-authors include Johanna Myrzik, Roland Szabó, Aurel Gontean, Katsunori Kawamura, Pavol Bauer, Viorel D. Popescu, Violeta Popescu and Bilel Selmi. Their work appears in journals such as Energies, Journal of Number Theory, Sensors, Journal of Mathematical Analysis and Applications and Electronics.

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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