P. Lipa

4.6k citations
49 papers · 2.1k indexed · h-index 21

P. Lipa

47 papers receiving 2.1k citations

Peers

P. Lipa
Comparison fields: 5 of 103
  • Cognitive Neuroscience 1.3k
  • Cellular and Molecular Neuroscience 1.2k
  • Developmental Neuroscience 183
  • Nuclear and High Energy Physics 360
  • Behavioral Neuroscience 95
Replace Georg B. Keller with:
Georg B. Keller Switzerland
Rubén Portugues Germany
P. Bonifazi Italy
Véronique Bernard France
Urs Gerber Switzerland
Fred Wolf Germany
Henrique von Gersdorff United States
K. I. Blum United States
William L. Kath United States
R. G. H. Robertson United States
P. Lipa relative to Georg B. Keller Switzerland Georg B. Keller's profile →
Citations per field
00.5×5.6×
Georg B. Keller · 1×
Citations per year

Countries citing papers authored by P. Lipa

Since Specialization
Citations

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

Fields of papers citing papers by P. Lipa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside P. Lipa, 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 P. Lipa Line = papers co-authored together P. Lipa links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201720
2 201634
3 201572
4 20155
5 20146
6 201323
7 201217
8 201232
9 201142
10 20076
11 2006142
12 200657
13 2005157
14 2005214
15 2005299
16 200416
17 2004200
18
Wavelets: from signal analysis to the analysis of complex processes.
19980
19 199312
20 199319

About P. Lipa

P. Lipa is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Nuclear and High Energy Physics, having authored 49 papers that have together received 2.1k indexed citations. Recurring topics across this work include Memory and Neural Mechanisms (17 papers), Neuroscience and Neuropharmacology Research (16 papers), High-Energy Particle Collisions Research (9 papers), Quantum Chromodynamics and Particle Interactions (9 papers), Particle physics theoretical and experimental studies (8 papers), Complex Systems and Time Series Analysis (6 papers), Neural dynamics and brain function (5 papers) and Image and Signal Denoising Methods (4 papers). The work is most often cited by research in Cognitive Neuroscience (1.3k citations), Cellular and Molecular Neuroscience (1.2k citations) and Developmental Neuroscience (183 citations). P. Lipa has collaborated with scholars based in United States, Austria and Germany. Frequent co-authors include Bruce L. McNaughton, B. Buschbeck, Carol A. Barnes, Monica K. Chawla, Paul Worley, John F. Guzowski, Andrew P. Maurer, Martin Greiner, H. C. Eggers and Gary R. Sutherland. Their work appears in journals such as Journal of Neuroscience, Physics Letters B, Hippocampus, The European Physical Journal C and Behavioral Neuroscience.

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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