TY - CHAP A1 - Cheron G. A2 - Duvinage M. A3 - Castermans A4 - T. Leurs F. A5 - Cebolla A. A6 - Bengoetxea A. A7 - De Saedeleer C. A8 - Petieau M. A9 - Hoellinger T. A10 - Seetharaman K. A11 - Draye JP. A12 - Dan B ED1 - Hubert Cardot Y1 - 2011-02-09 PY - 2011 T1 - Toward an Integrative Dynamic Recurrent Neural Network for Sensorimotor Coordination Dynamics N2 - The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving through time. Their internal memory gives them the ability to naturally take time into account. Valuable approximation results have been obtained for dynamical systems. BT - Recurrent Neural Networks for Temporal Data Processing SP - Ch. 5 UR - https://doi.org/10.5772/15977 DO - 10.5772/15977 SN - PB - IntechOpen CY - Rijeka Y2 - 2021-06-18 ER -