A. Pavasović

541 citations
16 papers · 415 · h-index 6

Impact in

Papers in

    • Advancements in Semiconductor Devices and Circuit Design 7
    • Advanced Memory and Neural Computing 5
    • Advanced MEMS and NEMS Technologies 2
    • Low-power high-performance VLSI design 2
    • Analog and Mixed-Signal Circuit Design 10
    • Acoustic Wave Resonator Technologies 2

A. Pavasović

14 papers receiving 391 citations

Peers

A. Pavasović
Comparison fields: 5 of 35
  • Electrical and Electronic Engineering 346
  • Cellular and Molecular Neuroscience 76
  • Cognitive Neuroscience 72
  • Artificial Intelligence 118
  • Hardware and Architecture 22
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Citations per field
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Citations per year

Countries citing papers authored by A. Pavasović

Since Specialization
Citations

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

Fields of papers citing papers by A. Pavasović

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 1991246
2 199471
3 199438
4 200216
5
Architectures for associative memories using current-mode analog MOS circuits
198910
6 20027
7
Current-Mode Subthreshold MOS Circuits for Analog
19915
8 19965
9 19964
10 20023
11 19953
12 19973
13 20042
14 20022
15 20020
16 20040

About A. Pavasović

A. Pavasović is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Cellular and Molecular Neuroscience, Artificial Intelligence and Computer Networks and Communications, having authored 16 papers that have together received 415 indexed citations. Recurring topics across this work include Analog and Mixed-Signal Circuit Design (10 papers), Advancements in Semiconductor Devices and Circuit Design (7 papers), Advanced Memory and Neural Computing (5 papers), Neuroscience and Neural Engineering (3 papers), Neural Networks and Applications (3 papers), Acoustic Wave Resonator Technologies (2 papers), Advanced MEMS and NEMS Technologies (2 papers) and Low-power high-performance VLSI design (2 papers). The work is most often cited by research in Electrical and Electronic Engineering (346 citations), Cellular and Molecular Neuroscience (76 citations), Cognitive Neuroscience (72 citations), Artificial Intelligence (118 citations) and Hardware and Architecture (22 citations). A. Pavasović has collaborated with scholars based in Serbia and United States. Frequent co-authors include Andreas G. Andreou, Kwabena Boahen, Philippe O. Pouliquen, K. Strohbehn, Robert E. Jenkins, Charles R. Westgate, Dragan Vasiljević, Jelena Popović and Branimir Reljin. Their work appears in journals such as IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, Analog Integrated Circuits and Signal Processing, International Journal of Circuit Theory and Applications, The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology and IEEE Transactions on Neural Networks.

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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