Mark Lammers

407 citations
16 papers · 197 · h-index 6

Impact in

Papers in

    • Mathematical Analysis and Transform Methods 13
    • Algebraic and Geometric Analysis 1
    • Digital Filter Design and Implementation 9
    • Blind Source Separation Techniques 1

Mark Lammers

16 papers receiving 190 citations

Peers

Mark Lammers
Comparison fields: 5 of 33
  • Applied Mathematics 130
  • Signal Processing 60
  • Computer Vision and Pattern Recognition 85
  • Computational Mechanics 79
  • Mathematical Physics 25
Replace Janet C. Tremain with:
Janet C. Tremain United States
Tim N.T. Goodman United Kingdom
H. G. Feichtinger Austria
Hong Oh Kim South Korea
Claire Boyer France
M.J. Ibáñez Spain
J.-C. Pesquet France
Xianliang Shi China
Giacomo Gigante Italy
Mark Lammers relative to Janet C. Tremain United States Janet C. Tremain's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mark Lammers

Since Specialization
Citations

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

Fields of papers citing papers by Mark Lammers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Mark Lammers, 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 Mark Lammers Line = papers co-authored together Mark Lammers links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 200441
2 201635
3 201229
4 200923
5 201022
6 200819
7 20055
8 20024
9 20104
10 20024
11 20073
12 20002
13 20142
14 20152
15 20101
16 20211

About Mark Lammers

Mark Lammers is a scholar working on Applied Mathematics, Signal Processing, Computer Vision and Pattern Recognition, Computational Mechanics and Mathematical Physics, having authored 16 papers that have together received 197 indexed citations. Recurring topics across this work include Mathematical Analysis and Transform Methods (13 papers), Image and Signal Denoising Methods (10 papers), Digital Filter Design and Implementation (9 papers), Sparse and Compressive Sensing Techniques (3 papers), Algebraic and Geometric Analysis (1 paper), Blind Source Separation Techniques (1 paper), Advanced Algebra and Geometry (1 paper) and Spectral Theory in Mathematical Physics (1 paper). The work is most often cited by research in Applied Mathematics (130 citations), Signal Processing (60 citations), Computer Vision and Pattern Recognition (85 citations), Computational Mechanics (79 citations) and Mathematical Physics (25 citations). Mark Lammers has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Peter G. Casazza, Özgür Yılmaz, Gitta Kutyniok, Alexander M. Powell, C. Si̇nan Güntürk, Rayan Saab, Karlheinz Gröchenig, Richard G. Lynch, James E. Blum and Ole Christensen. Their work appears in journals such as Journal of Fourier Analysis and Applications, Advances in Computational Mathematics, Foundations of Computational Mathematics, Journal of Mathematical Analysis and Applications and Applied and Computational Harmonic Analysis.

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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