Andrzej Tarczynski

720 citations
61 papers · 485 indexed · h-index 11

Andrzej Tarczynski

51 papers receiving 451 citations

Peers

Andrzej Tarczynski
Comparison fields: 5 of 69
  • Signal Processing 253
  • Computational Mechanics 176
  • Computer Vision and Pattern Recognition 111
  • Applied Mathematics 38
  • Computer Networks and Communications 64
Replace Abhijit Chandra with:
Abhijit Chandra India
Phillip A. Regalia United States
Adly T. Fam United States
K.M.M. Prabhu India
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Vanessa Su Lee Goh United Kingdom
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Citations per year

Countries citing papers authored by Andrzej Tarczynski

Since Specialization
Citations

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

Fields of papers citing papers by Andrzej Tarczynski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 19 scholars most cited alongside Andrzej Tarczynski, 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 Andrzej Tarczynski Line = papers co-authored together Andrzej Tarczynski links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20215
2 20172
3 20166
4 20121
5 20117
6 201014
7
Sub-Landau sampling of Multiband signals and designing Periodic Nonuniform Sampling
20070
8 20077
9
Analysis and design of WPNS sequences for digital alias-free signal processing
20061
10
Reliability of signal reconstruction from arbitrarily distributed noisy samples
20062
11 20060
12
Quality assessment of reconstructing signals from arbitrarily distributed samples
20060
13
OPTIMAL RANDOM SAMPLING FOR SPECTRUM ESTIMATION IN DASP APPLICATIONS
200514
14
Reconstruction of nonuniformly sampled periodic signals
20032
15 20030
16
Signal reconstruction from finite sets of arbitrarily distributed samples
20021
17 200221
18 20025
19 200247
20 20023

About Andrzej Tarczynski

Andrzej Tarczynski is a scholar working on Signal Processing, Computational Mechanics, Computer Vision and Pattern Recognition, Applied Mathematics and Computer Networks and Communications, having authored 61 papers that have together received 485 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (17 papers), Image and Signal Denoising Methods (15 papers), Digital Filter Design and Implementation (14 papers), Sparse and Compressive Sensing Techniques (13 papers), Advanced Adaptive Filtering Techniques (11 papers), Advanced Electrical Measurement Techniques (10 papers), Distributed Sensor Networks and Detection Algorithms (8 papers) and Target Tracking and Data Fusion in Sensor Networks (6 papers). The work is most often cited by research in Signal Processing (253 citations), Computational Mechanics (176 citations), Computer Vision and Pattern Recognition (111 citations), Applied Mathematics (38 citations) and Computer Networks and Communications (64 citations). Andrzej Tarczynski has collaborated with scholars based in United Kingdom, Poland and Greece. Frequent co-authors include G.D. Cain, E. Hermanowicz, Bashar I. Ahmad, J.N. Lygouras, H.S. Chowdrey, Vassilis Kodogiannis, Vesa Välimäki, T.I. Laakso, Paul E. Murphy and Timo Laakso. Their work appears in journals such as Signal Processing, IEEE Transactions on Signal Processing, Digital Signal Processing, Future Generation Computer Systems and Automatica.

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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