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Control of a subsonic electropneumatic acoustic generator with dynamic recurrent neural networks., , and . ESANN, page 67-72. (1998)Negative initial weights improve learning in recurrent neural networks., , , , , and . ESANN, (1996)Motor strategies in standing up in children with hemiplegia., , , , , and . Pediatr Neurol, 30 (4): 257--261 (April 2004)Identification of the human arm kinetics using dynamic recurrent neural networks., , , , and . ESANN, (1995)Are current gait-related artifact removal techniques useful for low-complexity BCIs?, , , , and . IJCNN, page 1-7. IEEE, (2012)EEG and Human Locomotion - Descending Commands and Sensory Feedback should be Disentangled from Artifacts Thanks to New Experimental Protocols Position Paper., , , and . BIOSIGNALS, page 309-314. SciTePress, (2012)Improved Identification of the Human Shoulder Kinematics with Muscle Biological Filters., , , and . AIME, volume 1211 of Lecture Notes in Computer Science, page 417-428. Springer, (1997)An efficient learning model for the neural integrator of the oculomotor system., , , and . ESANN, (1993)Adaptative time constants improve the dynamic features of recurrent neural networks., , , and . ESANN, (1996)Evidence of efficiency of recurrent neural networks with ARMA-like units., , , and . ESANN, D-Facto public, (1997)