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Immune-Inspired Optimization with Autocorrentropy Function for Blind Inversion of Wiener Systems., , , , and . CEC, page 1-7. IEEE, (2018)Data mining tool to discover DevOps trends from public repositories: Predicting Release Candidates with gthbmining.rc., , and . SBES, page 658-663. ACM, (2020)Error entropy criterion in echo state network training., , , , , , , , and . ESANN, (2013)Blind separation of convolutive mixtures over Galois fields., , , , , , and . MLSP, page 1-6. IEEE, (2013)Artifact removal for emotion recognition using mutual information and Epanechnikov kernel., , , , , , and . Biomed. Signal Process. Control., (May 2023)EvoMan: Game-playing Competition., , , , and . CoRR, (2019)Classification of image encoded SSVEP-based EEG signals using Convolutional Neural Networks., , , and . Expert Syst. Appl., (2023)Epanechnikov kernel for PDF estimation applied to equalization and blind source separation., , and . Signal Process., (2021)An Immune-Inspired, Dependence-Based Approach to Blind Inversion of Wiener Systems., , , , and . ESANN, (2016)Using Taylor Series Expansions and Second-Order Statistics for Blind Source Separation in Post-Nonlinear Mixtures., , , , , and . LVA/ICA, volume 10891 of Lecture Notes in Computer Science, page 193-203. Springer, (2018)