| Wavelet based shock wave and muzzle blast classification for different supersonic projectiles U Libal, K Spyra Expert Systems with Applications 41 (11), 5097-5104, 2014 | 23 | 2014 |
| Risk upper bound for a NM-type multiresolution classification scheme of random signals by Daubechies wavelets U Libal, Z Hasiewicz Engineering Applications of Artificial Intelligence 62, 109-123, 2017 | 12 | 2017 |
| Nonlinear Schur-type orthogonal transformations of higher-order stochastic processes: An overview of current topics J Zarzycki, A Wielgus, U Libal 2017 Signal Processing Symposium (SPSympo), 1-5, 2017 | 10 | 2017 |
| Noise sensitivity of selected kinematic path following controllers for a unicycle U Libal, J Płaskonka Bulletin of the Polish Academy of Sciences. Technical Sciences 62 (1), 3-13, 2014 | 9 | 2014 |
| Feature selection for pattern recognition by LASSO and thresholding methods-a comparison U Libal 2011 16th International Conference on Methods & Models in Automation …, 2011 | 9 | 2011 |
| Nonlinear Orthogonal Parametrization and Modeling of Higher-Order Non-Gaussian Time-Series U Libal, A Wielgus, W Magiera Signal Processing Symposium (SPSympo-2017), 2017 | 7 | 2017 |
| Multistage classification of signals with the use of multiscale wavelet representation U Libal 2010 15th International Conference on Methods and Models in Automation and …, 2010 | 7 | 2010 |
| Nonlinear Complexity Reduction: Sparsity of the Generalized Schur Coefficient Matrices and Frobenius Norm Criterion A Wielgus, U Libal, W Magiera Signal Processing Symposium (SPSympo-2017), 2017 | 6 | 2017 |
| Yule-Walker equations using higher order statistics for nonlinear autoregressive model U Libal, KH Johansson 2019 Signal Processing Symposium (SPSympo), 227-231, 2019 | 5 | 2019 |
| Wavelet based rule for fault detection U Libal, Z Hasiewicz IFAC-PapersOnLine 51 (24), 255-262, 2018 | 5 | 2018 |
| Generalized Schur Parametrization and Orthogonal Modeling Algorithms For Second-Order Time-Series U Libal, W Magiera, A Wielgus Signal Processing Symposium (SPSympo-2017), 2017 | 5 | 2017 |
| Multistage pattern recognition of signals represented in wavelet bases with reject option U Libal Methods and Models in Automation and Robotics (MMAR), 2012 17th …, 2012 | 4 | 2012 |
| An Automatic Analysis System for High-Throughput Clostridium Difficile Toxin Activity Screening M Garland, J Jaworek-Korjakowska, U Libal, M Bogyo, M Sieńczyk Applied Sciences 8 (9), 1512, 2018 | 3 | 2018 |
| Multistage Naive Bayes Classifier with Reject Option for Multiresolution Signal Representation U Libal ICPRAM 2013: Proceedings of the 2nd International Conference on Pattern …, 2013 | 3 | 2013 |
| Detecting drones at an entrance to a beehive based on audio signals and autoencoder neural networks U Libal, P Biernacki 2023 Signal Processing Symposium (SPSympo), 99-104, 2023 | 1 | 2023 |
| Pattern recognition using adaptive schur-like parametrization of signals with forgetting factor U Libal 2018 International Conference on Signals and Electronic Systems (ICSES), 151-156, 2018 | 1 | 2018 |
| Quality evaluation of isotropic electromagnetic field probes using classification trees B Zubrzak, P Bieńkowski, U Libal 2018 28th International Conference Radioelektronika (RADIOELEKTRONIKA), 1-5, 2018 | 1 | 2018 |
| Efficient measurement of higher-order statistics of stochastic processes W Magiera, U Libal, A Wielgus Kybernetika 54 (5), 865-887, 2018 | 1 | 2018 |
| Comparison of keypoint detection methods for indoor and outdoor scene recognition U Libal, Ł Łoziuk Journal of Automation Mobile Robotics and Intelligent Systems 11, 2017 | 1 | 2017 |
| Wavelet algorithm for hierarchical pattern recognition U Libal, Z Hasiewicz Stochastic Models, Statistics and Their Applications: Wrocław, Poland …, 2015 | 1 | 2015 |
Karl H. JohanssonEECS and Digital Futures, KTH Royal Institute of Technology, SwedenVerified email at kth.se
