E. Lantto

721 citations
15 papers · 525 · h-index 9

Impact in

Papers in

E. Lantto

14 papers receiving 452 citations

Peers

E. Lantto
Comparison fields: 5 of 32
  • Control and Systems Engineering 429
  • Mechanical Engineering 245
  • Electronic, Optical and Magnetic Materials 108
  • Electrical and Electronic Engineering 331
  • General Materials Science 13
Replace Andrea Tortella with:
Andrea Tortella Italy
Timo Holopainen Finland
Alexei Filatov United States
Yun‐Hyun Cho South Korea
Md Nishat Anwar India
Xinggang Fan China
Giuseppe Fabri Italy
Mariusz Jagieła Poland
Jeroen de Boeij Netherlands
E. Lantto relative to Andrea Tortella Italy Andrea Tortella's profile →
Citations per field
00.5×4.3×
Andrea Tortella · 1×
Citations per year

Countries citing papers authored by E. Lantto

Since Specialization
Citations

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

Fields of papers citing papers by E. Lantto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside E. Lantto, 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 E. Lantto Line = papers co-authored together E. Lantto links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
Active Magnetic Bearings
2007120
2 200579
3 200071
4
Robust control of magnetic bearings in subcritical machines
199952
5 200051
6 199849
7 201633
8 200531
9 200517
10 20047
11 20096
12
Electromagnetic forces caused by cage induction motor
20004
13
On convergence problems of adaptive fir filter with lms algorithm
20092
14
Inverse problems of magnetic bearing dynamics
19942
15 20031

About E. Lantto

E. Lantto is a scholar working on Control and Systems Engineering, Electrical and Electronic Engineering, Mechanical Engineering, Electronic, Optical and Magnetic Materials and Aerospace Engineering, having authored 15 papers that have together received 525 indexed citations. Recurring topics across this work include Magnetic Bearings and Levitation Dynamics (13 papers), Electric Motor Design and Analysis (10 papers), Magnetic Properties and Applications (4 papers), Tribology and Lubrication Engineering (4 papers), Electric Power Systems and Control (3 papers), Inertial Sensor and Navigation (2 papers), Sensorless Control of Electric Motors (2 papers) and Adhesion, Friction, and Surface Interactions (1 paper). The work is most often cited by research in Control and Systems Engineering (429 citations), Mechanical Engineering (245 citations), Electronic, Optical and Magnetic Materials (108 citations), Electrical and Electronic Engineering (331 citations) and General Materials Science (13 citations). E. Lantto has collaborated with scholars based in Finland and Italy. Frequent co-authors include Antero Arkkio, Tapani Jokinen, Adam C. Simon, A. Tenhunen, Timo Holopainen, Antti Lehikoinen, Anouar Belahcen, Kari Tammi and Kai Zenger. Their work appears in journals such as IEEE Transactions on Magnetics, Journal of vibration and acoustics, Electrical Engineering, IEE Proceedings - Electric Power Applications and Journal of System Design and Dynamics.

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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