New Experimental Results in Differential - Linear Cryptanalysis of Reduced Variants of DES. - Anna Górska; Karol Górski; Zbigniew Kotulski; Andrzej Paszkiewicz; Janusz Szczepanski (ACS, 2001)

Pseudorandom Number Generators Based on Chaotic Dynamical Systems. - Janusz Szczepanski; Zbigniew Kotulski (Open Syst. Inf. Dyn., 2001)

Approximations of Dynamical Systems and their Applications to Cryptography. - José M. Amigó; Janusz Szczepanski (Int. J. Bifurc. Chaos, 2003)

Biometric random number generators. - Janusz Szczepanski; Elek Wajnryb; José M. Amigó; Maria V. Sanchez-Vives; Mel Slater (Comput. Secur., 2004)

Characterizing spike trains with Lempel-Ziv complexity. - Janusz Szczepanski; José M. Amigó; Elek Wajnryb; Maria V. Sanchez-Vives (Neurocomputing, 2004)

Estimating the Entropy Rate of Spike Trains via Lempel-Ziv Complexity. - José M. Amigó; Janusz Szczepanski; Elek Wajnryb; Maria V. Sanchez-Vives (Neural Comput., 2004)

Cryptographically secure substitutions based on the approximation of mixing maps. - Janusz Szczepanski; José María Amigó; Tomasz Michalek; Ljupco Kocarev (IEEE Trans. Circuits Syst. I Regul. Pap., 2005)

Discrete Chaos-I: Theory. - Ljupco Kocarev; Janusz Szczepanski; José María Amigó; Igor Tomovski (IEEE Trans. Circuits Syst. I Regul. Pap., 2006)

Discrete Lyapunov Exponent and Resistance to Differential Cryptanalysis. - José María Amigó; Ljupco Kocarev; Janusz Szczepanski (IEEE Trans. Circuits Syst. II Express Briefs, 2007)

On the distribution function of the complexity of finite sequences. - Janusz Szczepanski (Inf. Sci., 2009)

Mutual information and redundancy in spontaneous communication between cortical neurons. - Janusz Szczepanski; M. Arnold; Elek Wajnryb; José M. Amigó; Maria V. Sanchez-Vives (Biol. Cybern., 2011)

Efficiency of neural transmission as a function of synaptic noise, threshold, and source characteristics. - Bartosz Paprocki; Janusz Szczepanski (Biosyst., 2011)

How do the amplitude fluctuations affect the neuronal transmission efficiency. - Bartosz Paprocki; Janusz Szczepanski (Neurocomputing, 2013)

A Proposal for a Method of Defuzzification Based on the Golden Ratio - GR. - Wojciech T. Dobrosielski; Janusz Szczepanski; Hubert Zarzycki (IWIFSGN@FQAS, 2015)

Temporal code versus rate code for binary Information Sources. - Agnieszka Pregowska; Janusz Szczepanski; Eligiusz Wajnryb (Neurocomputing, 2016)

Fuzzy Numbers Applied to a Heat Furnace Control. - Wojciech T. Dobrosielski; Jacek M. Czerniak; Hubert Zarzycki; Janusz Szczepanski (Theory and Applications of Ordered Fuzzy Numbers, 2017)

Triangular Expanding, A New Defuzzification Method on Ordered Fuzzy Numbers. - Wojciech T. Dobrosielski; Jacek M. Czerniak; Janusz Szczepanski; Hubert Zarzycki (EUSFLAT/IWIFSGN (1), 2017)

New Fuzzy Numbers Comparison Operators In Energy Effectiveness Simulation And Modeling Systems. - Wojciech T. Dobrosielski; Jacek M. Czerniak; Hubert Zarzycki; Janusz Szczepanski (ECMS, 2018)

Information processing in the LGN: a comparison of neural codes and cell types. - Agnieszka Pregowska; Alex Casti; Ehud Kaplan; Eligiusz Wajnryb; Janusz Szczepanski (Biol. Cybern., 2019)

Using Lempel-Ziv complexity as effective classification tool of the sleep-related breathing disorders. - Agnieszka Pregowska; Klaudia Proniewska; Peter M. van Dam; Janusz Szczepanski (Comput. Methods Programs Biomed., 2019)

How Far can Neural Correlations Reduce Uncertainty? Comparison of Information Transmission Rates for Markov and Bernoulli Processes. - Agnieszka Pregowska; Ehud Kaplan; Janusz Szczepanski (Int. J. Neural Syst., 2019)

Does Adding of Neurons to the Network Layer Lead to Increased Transmission Efficiency? - Bartosz Paprocki; Agnieszka Pregowska; Janusz Szczepanski (IEEE Access, 2024)

Bio-Inspired Classification: Combining Information Theory and Spiking Neural Networks - Influence of the Learning Rules. - Zofia Rudnicka; Janusz Szczepanski; Agnieszka Pregowska (CoRR, 2025)