Janusz Szczepański

1.3k total citations
50 papers, 916 citations indexed

About

Janusz Szczepański is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Janusz Szczepański has authored 50 papers receiving a total of 916 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Statistical and Nonlinear Physics, 17 papers in Cognitive Neuroscience and 15 papers in Computer Vision and Pattern Recognition. Recurrent topics in Janusz Szczepański's work include Neural dynamics and brain function (16 papers), Chaos-based Image/Signal Encryption (15 papers) and stochastic dynamics and bifurcation (8 papers). Janusz Szczepański is often cited by papers focused on Neural dynamics and brain function (16 papers), Chaos-based Image/Signal Encryption (15 papers) and stochastic dynamics and bifurcation (8 papers). Janusz Szczepański collaborates with scholars based in Poland, Spain and United States. Janusz Szczepański's co-authors include José M. Amigó, Ljupčo Kocarev, María V. Sánchez-Vives, Eligiusz Wajnryb, Zbigniew Kotulski, Agnieszka Pręgowska, Andrzej Paszkiewicz, Mel Slater, Magdalena Osial and Magdalena Garlińska and has published in prestigious journals such as Physical Review Letters, Brain Research and Physical Review A.

In The Last Decade

Janusz Szczepański

47 papers receiving 837 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Janusz Szczepański Poland 15 402 332 244 205 172 50 916
Hayder Natiq India 21 443 1.1× 814 2.5× 197 0.8× 167 0.8× 78 0.5× 88 1.3k
Huihai Wang China 25 556 1.4× 1.3k 4.0× 272 1.1× 321 1.6× 129 0.8× 97 1.8k
Nestor Tsafack Cameroon 21 782 1.9× 665 2.0× 298 1.2× 172 0.8× 164 1.0× 43 1.4k
Abdul Jalil M. Khalaf Iraq 18 182 0.5× 922 2.8× 79 0.3× 186 0.9× 145 0.8× 62 1.2k
Yuanyuan Huang China 24 625 1.6× 899 2.7× 276 1.1× 140 0.7× 166 1.0× 50 1.5k
Yicheng Zeng China 20 323 0.8× 967 2.9× 147 0.6× 139 0.7× 53 0.3× 66 1.2k
Seyed Mohammad Reza Hashemi Golpayegani Iran 17 162 0.4× 1.2k 3.6× 120 0.5× 191 0.9× 25 0.1× 36 1.4k
Toni Stojanovski North Macedonia 14 579 1.4× 804 2.4× 242 1.0× 42 0.2× 286 1.7× 26 1.2k
Ralf Der Germany 14 124 0.3× 154 0.5× 394 1.6× 251 1.2× 64 0.4× 59 798

Countries citing papers authored by Janusz Szczepański

Since Specialization
Citations

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

Fields of papers citing papers by Janusz Szczepański

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Janusz Szczepański

This figure shows the co-authorship network connecting the top 25 collaborators of Janusz Szczepański. A scholar is included among the top collaborators of Janusz Szczepański based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Janusz Szczepański. Janusz Szczepański is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Garlińska, Magdalena, et al.. (2021). Experimental Study of the Free Space Optics Communication System Operating in the 8–12 µm Spectral Range. Electronics. 10(8). 875–875. 20 indexed citations
2.
Błoński, Sławomir, et al.. (2019). The use of Lempel-Ziv complexity to analyze turbulence and flow randomness based on velocity fluctuations. Bulletin of the Polish Academy of Sciences Technical Sciences. 957–962. 2 indexed citations
3.
Pręgowska, Agnieszka, Klaudia Proniewska, Peter van Dam, & Janusz Szczepański. (2019). Using Lempel-Ziv complexity as effective classification tool of the sleep-related breathing disorders. Computer Methods and Programs in Biomedicine. 182. 105052–105052. 10 indexed citations
4.
Pręgowska, Agnieszka, et al.. (2019). Information processing in the LGN: a comparison of neural codes and cell types. Biological Cybernetics. 113(4). 453–464. 7 indexed citations
5.
Pręgowska, Agnieszka, Janusz Szczepański, & Eligiusz Wajnryb. (2015). Mutual information against correlations in binary communication channels. BMC Neuroscience. 16(1). 32–32. 14 indexed citations
6.
Szczepański, Janusz, et al.. (2013). Transmission efficiency in ring, brain inspired neuronal networks. Information and energetic aspects. Brain Research. 1536. 135–143. 6 indexed citations
7.
Szczepański, Janusz, et al.. (2012). Information content in cortical spike trains during brain state transitions. Journal of Sleep Research. 22(1). 13–21. 12 indexed citations
8.
Szczepański, Janusz, et al.. (2011). Efficiency of neural transmission as a function of synaptic noise, threshold, and source characteristics. Biosystems. 105(1). 62–72. 9 indexed citations
9.
Szczepański, Janusz, et al.. (2011). Mutual information and redundancy in spontaneous communication between cortical neurons. Biological Cybernetics. 104(3). 161–174. 14 indexed citations
10.
Kocarev, Ljupčo, et al.. (2005). Discrete Chaos – Part I: Theory. 1 indexed citations
11.
Szczepański, Janusz, Eligiusz Wajnryb, José M. Amigó, María V. Sánchez-Vives, & Mel Slater. (2004). Biometric random number generators. Computers & Security. 23(1). 77–84. 42 indexed citations
12.
Amigó, José M., et al.. (2004). Estimating the Entropy Rate of Spike Trains via Lempel-Ziv Complexity. Neural Computation. 16(4). 717–736. 115 indexed citations
13.
Szczepański, Janusz, José M. Amigó, Eligiusz Wajnryb, & María V. Sánchez-Vives. (2004). Characterizing spike trains with Lempel–Ziv complexity. Neurocomputing. 58-60. 79–84. 32 indexed citations
14.
Amigó, José M., Janusz Szczepański, Eligiusz Wajnryb, & María V. Sánchez-Vives. (2003). On the number of states of the neuronal sources. Biosystems. 68(1). 57–66. 12 indexed citations
15.
Amigó, José M. & Janusz Szczepański. (2003). Approximations of Dynamical Systems and Their Applications to Cryptography. International Journal of Bifurcation and Chaos. 13(7). 1937–1948. 5 indexed citations
16.
Szczepański, Janusz. (2001). A new result on the Nirenberg problem for expanding maps. Nonlinear Analysis. 43(1). 91–99. 4 indexed citations
17.
Kotulski, Zbigniew & Janusz Szczepański. (1999). On the application of discrete chaotic systems to cryptography : DCC method. Bulletin of the Military University of Technology. 48. 111–122.
18.
Szczepański, Janusz, et al.. (1999). Some models of chaotic motion of particles and their application to cryptography. Archives of Mechanics. 51. 509–528. 4 indexed citations
19.
Szczepański, Janusz & Zbigniew Kotulski. (1998). On two motions of a particle driven by equivalent ergodic and chaotic reflection laws. Archives of Mechanics. 50(5). 865–875. 3 indexed citations
20.
Szczepański, Janusz. (1989). On the basis of statistical mechanics. The Liouville equation for systems with an infinite countable number of degrees of freedom. Physica A Statistical Mechanics and its Applications. 157(2). 955–982. 2 indexed citations

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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