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Evaluation of Fitting Functions for the Saccade Velocity Profile in Electrooculographic Records.

, , , , , , , and . IWANN (2), volume 9095 of Lecture Notes in Computer Science, page 592-600. Springer, (2015)

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Neural Net with Two Hidden Layers for Non-Linear Blind Source Separation., , , , and . ESANN, page 137-142. (2003)Evaluation of Fitting Functions for the Saccade Velocity Profile in Electrooculographic Records., , , , , , , and . IWANN (2), volume 9095 of Lecture Notes in Computer Science, page 592-600. Springer, (2015)Automatic Glissade Determination Through a Mathematical Model in Electrooculographic Records., , , , and . IWBBIO (1), volume 10208 of Lecture Notes in Computer Science, page 546-556. (2017)Evaluation of electro-oculography data for ataxia SCA-2 classification: A blind source separation approach., , , , , , and . ISDA, page 237-241. IEEE, (2010)Lattice ICA for the separation of speech signals., , , , , and . ESANN, page 337-342. (2004)Evaluation of Algorithms for Automatic Classification of Heart Sound Signals., , , , and . IWBBIO (1), volume 10208 of Lecture Notes in Computer Science, page 536-545. (2017)Analysis of Variance of Three Contrast Functions in a Genetic Algorithm for Non-linear Blind Source Separation., , and . IWANN, volume 3512 of Lecture Notes in Computer Science, page 1043-1050. Springer, (2005)Automatic glissade determination through a mathematical model in electrooculographic records., , , , and . CoRR, (2021)Automatic classification of prostate cancer using pseudo-gaussian radial basis function neural network., , , and . ESANN, page 145-150. (2005)Analysis of contrast functions in a genetic algorithm for post-nonlinear blind source separation., , and . ESANN, page 521-526. (2005)