Application of entropy and energy measures of fuzziness to processing of ECG signal. - Ernest Czogala; Jacek M. Leski (Fuzzy Sets Syst., 1998)

A new artificial neural network based fuzzy inference system with moving consequents in if-then rules and selected applications. - Jacek M. Leski; Ernest Czogala (Fuzzy Sets Syst., 1999)

A Classifier Based on Neuro-Fuzzy Inference System Ernest. - Ernest Czogala; Jacek M. Leski; Yoichi Hayashi (J. Adv. Comput. Intell. Intell. Informatics, 1999)

Fuzzy and Neuro-Fuzzy Intelligent Systems - Ernest Czogala; Jacek M. Leski (Springer, 2000)

On equivalence of approximate reasoning results using different interpretations of fuzzy if-then rules. - Ernest Czogala; Jacek M. Leski (Fuzzy Sets Syst., 2001)

Robust weighted averaging [of biomedical signals]. - Jacek M. Leski (IEEE Trans. Biomed. Eng., 2002)

Towards a robust fuzzy clustering. - Jacek M. Leski (Fuzzy Sets Syst., 2003)

Neuro-fuzzy system with learning tolerant to imprecision. - Jacek M. Leski (Fuzzy Sets Syst., 2003)

Ho-Kashyap classifier with generalization control. - Jacek M. Leski (Pattern Recognit. Lett., 2003)

Generalized weighted conditional fuzzy clustering. - Jacek M. Leski (IEEE Trans. Fuzzy Syst., 2003)

A New Fuzzy Clustering Method with Constraints in Time Domain. - Jacek M. Leski; Aleksander J. Owczarek (ICAISC, 2004)

Fuzzy c-varieties/elliptotypes clustering in reproducing kernel Hilbert space. - Jacek M. Leski (Fuzzy Sets Syst., 2004)

Computationally effective algorithm for robust weighted averaging. - Jacek M. Leski; Adam Gacek (IEEE Trans. Biomed. Eng., 2004)

ε-insensitive fuzzy c-regression models: introduction to ε-insensitive fuzzy modeling. - Jacek M. Leski (IEEE Trans. Syst. Man Cybern. Part B, 2004)

An ε-margin nonlinear classifier based on fuzzy if-then rules. - Jacek M. Leski (IEEE Trans. Syst. Man Cybern. Part B, 2004)

A Hybrid epsilon-Insensitive Learning of Fuzzy Systems. - Tomasz Czogala; Jacek M. Leski (CORES, 2005)

Multi-Channels Time-Domain-Constrained Fuzzy c -Regression Models. - Aleksander J. Owczarek; Adam Gacek; Jacek M. Leski (CORES, 2005)

A time-domain-constrained fuzzy clustering method and its application to signal analysis. - Jacek M. Leski; Aleksander J. Owczarek (Fuzzy Sets Syst., 2005)

ECG baseline wander and powerline interference reduction using nonlinear filter bank. - Jacek M. Leski; Norbert Henzel (Signal Process., 2005)

TSK-fuzzy modeling based on ε-insensitive learning. - Jacek M. Leski (IEEE Trans. Fuzzy Syst., 2005)

On support vector regression machines with linguistic interpretation of the kernel matrix. - Jacek M. Leski (Fuzzy Sets Syst., 2006)

The Prediction of Fetal Outcome by Applying Neural Network for Evaluation of CTG Records. - Michal Jezewski; Janusz Wrobel; Krzysztof Horoba; Adam Gacek; Norbert Henzel; Jacek M. Leski (Computer Recognition Systems 2, 2008)

An Application of Fuzzy Clustering Method to Cardiotocographic Signals Classification. - Michal Jezewski; Jacek M. Leski (ICMMI, 2011)

Fuzzy Clustering Finding Prototypes on Classes Boundary. - Michal Jezewski; Jacek M. Leski (Computer Recognition Systems 4, 2011)

Robust Estimation of Respiratory Rate Based on Linear Regression. - Jacek M. Leski; Norbert Henzel; Alina Momot; Michal Momot; Joanna Sledzik (Computer Recognition Systems 4, 2011)

Generalized Constraint Design of Linear-Phase FIR Digital Filters. - Norbert Henzel; Jacek M. Leski (CORES, 2013)

Nonlinear Extension of the IRLS Classifier Using Clustering with Pairs of Prototypes. - Michal Jezewski; Jacek M. Leski (CORES, 2013)

Time Series of Fuzzy Sets in Classification of Electrocardiographic Signals. - Jacek M. Leski; Norbert Henzel (CORES, 2013)

Design of Linear-Phase FIR Filters with Time and Frequency Domains Constraints by Means of AI Based Method. - Norbert Henzel; Jacek M. Leski (ICMMI, 2013)

Application of the Conditional Fuzzy Clustering with Prototypes Pairs to Classification. - Michal Jezewski; Jacek M. Leski (ICMMI, 2013)

An Application of Fuzzy C-Regression Models to Characteristic Point Detection in Biomedical Signals. - Alina Momot; Michal Momot; Jacek M. Leski (ICMMI, 2013)

Classification Based on Incremental Fuzzy (1+p) ( 1 + p ) -Means Clustering. - Michal Jezewski; Jacek M. Leski; Robert Czabanski (ICMMI, 2015)

Dynamic Time Warping Based on Modified Alignment Costs for Evoked Potentials Averaging. - Marian Kotas; Jacek M. Leski; Tomasz Moron (ICMMI, 2015)

PCA Based Hierarchical Clustering with Planar Segments as Prototypes and Maximum Density Linkage. - Jacek M. Leski; Marian Kotas; Tomasz Moron (ICMMI, 2015)

Principal Component Analysis and Dynamic Time-Warping in Subbands for ECG Reconstruction. - Tomasz Moron; Marian Kotas; Jacek M. Leski (ICMMI, 2015)

Averaging of nonlinearly aligned signal cycles for noise suppression. - Marian Kotas; Tomasz Pander; Jacek M. Leski (Biomed. Signal Process. Control., 2015)

On robust fuzzy c-regression models. - Jacek M. Leski; Marian Kotas (Fuzzy Sets Syst., 2015)

Hierarchical clustering with planar segments as prototypes. - Jacek M. Leski; Marian Kotas (Pattern Recognit. Lett., 2015)

Fuzzy (c+p)-Means Clustering and Its Application to a Fuzzy Rule-Based Classifier: Toward Good Generalization and Good Interpretability. - Jacek M. Leski (IEEE Trans. Fuzzy Syst., 2015)

Fuzzy Analysis of Delivery Outcome Attributes for Improving the Automated Fetal State Assessment. - Robert Czabanski; Michal Jezewski; Krzysztof Horoba; Janusz Jezewski; Jacek M. Leski (Appl. Artif. Intell., 2016)

Clustering with Pairs of Prototypes to Support Automated Assessment of the Fetal State. - Michal Jezewski; Robert Czabanski; Krzysztof Horoba; Jacek M. Leski (Appl. Artif. Intell., 2016)

Fuzzy c-ordered-means clustering. - Jacek M. Leski (Fuzzy Sets Syst., 2016)

Fuzzy c-ordered medoids clustering for interval-valued data. - Pierpaolo D'Urso; Jacek M. Leski (Pattern Recognit., 2016)

Introduction to Fuzzy Systems. - Robert Czabanski; Michal Jezewski; Jacek M. Leski (Theory and Applications of Ordered Fuzzy Numbers, 2017)

Introduction to Fuzzy Sets. - Michal Jezewski; Robert Czabanski; Jacek M. Leski (Theory and Applications of Ordered Fuzzy Numbers, 2017)

Fuzzy Clustering with varepsilon -Hyperballs and Its Application to Data Classification. - Michal Jezewski; Robert Czabanski; Jacek M. Leski (ICAISC (2), 2017)

Hierarchical Agglomerative Clustering of Time-Warped Series. - Marian Kotas; Jacek M. Leski; Tomasz Moron; Jader Giraldo-Guzmán (ICMMI, 2017)

Averaging of Nonlinearly Aligned Evoked Potentials in Impulsive Noise Environment. - Marian Kotas; Tomasz Pander; Jacek M. Leski; Tomasz Moron (ICMMI, 2017)

Linguistically Defined Clustering of Data. - Jacek M. Leski; Marian Kotas (Int. J. Appl. Math. Comput. Sci., 2018)

On clustering based nonlinear projective filtering of biomedical signals. - Tomasz Przybyla; Marian Kotas; Jacek M. Leski (Biomed. Signal Process. Control., 2018)

Recognition of Atrial Fibrilation Episodes in Heart Rate Variability Signals Using a Machine Learning Approach. - Krzysztof Horoba; Robert Czabanski; Janusz Wrobel; Adam Matonia; Radek Martinek; Tomasz Kupka; Radana Kahankova; Jacek M. Leski; Slawomir Graczyk (MIXDES, 2019)

Application of Spatio-Temporal Filtering for Atrial Activity Waveforms Enhancement. - Jader Giraldo-Guzmán; Marian Kotas; Michal Piela; Francisco Castells; Jacek M. Leski; Sonia H. Contreras Ortiz (SSIP, 2019)

Fuzzy classifier based on clustering with pairs of ε-hyperballs and its application to support fetal state assessment. - Michal Jezewski; Robert Czabanski; Jacek M. Leski; Janusz Jezewski (Expert Syst. Appl., 2019)

Clustering with ε-Hyperballs Based Simplification of Fuzzy Rules to Support the Assessment of Fetal State. - Robert Czabanski; Michal Jezewski; Jacek M. Leski; Tomasz Kupka; Radek Martinek (BIBE, 2020)

Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals. - Michal Jezewski; Robert Czabanski; Jacek M. Leski; Adam Matonia; Radek Martinek (MIXDES, 2020)

Fuzzy clustering of fuzzy data based on robust loss functions and ordered weighted averaging. - Pierpaolo D'Urso; Jacek M. Leski (Fuzzy Sets Syst., 2020)

Detection of Atrial Fibrillation Episodes in Long-Term Heart Rhythm Signals Using a Support Vector Machine. - Robert Czabanski; Krzysztof Horoba; Janusz Wrobel; Adam Matonia; Radek Martinek; Tomasz Kupka; Michal Jezewski; Radana Kahankova; Janusz Jezewski; Jacek M. Leski (Sensors, 2020)

Fuzzy Ordered $c$-Means Clustering and Least Angle Regression for Fuzzy Rule-Based Classifier: Study for Imbalanced Data. - Jacek M. Leski; Robert Czabanski; Michal Jezewski; Janusz Jezewski (IEEE Trans. Fuzzy Syst., 2020)

Robust nonlinear aggregation operator for ECG powerline interference reduction. - Jacek M. Leski (Biomed. Signal Process. Control., 2021)

On ε-insensitive simplification of fuzzy rules for fetal distress assessment. - Michal Jezewski; Robert Czabanski; Jacek M. Leski; Adam Matonia; Radana Kahankova (Expert Syst. Appl., 2021)

Practical aspects of equivalence of Baldwin's and Zadeh's fuzzy inference. - Przemyslaw Kudlacik; Jacek M. Leski (J. Intell. Fuzzy Syst., 2021)

Clustering based multiple state-space projections. - Marian Kotas; Adam Dyrek; Michal Piela; Jacek M. Leski (Signal Process., 2021)

Fuzzy double-ordered c-regression models based on fuzzy S-estimators. - Jacek M. Leski (Fuzzy Sets Syst., 2023)

Refining the rule base of fuzzy classifier to support the evaluation of fetal condition. - Robert Czabanski; Michal Jezewski; Jacek M. Leski; Krzysztof Horoba; Janusz Wrobel; Radek Martinek; Katerina Barnova (Appl. Soft Comput., 2023)

OWA-based robust fuzzy clustering of time series with typicality degrees. - Pierpaolo D'Urso; Jacek M. Leski (Inf. Sci., 2023)