Sequence learning using the neural coding

@incollection{citeulike:2910635, abstract = {This article introduces a neural network capable of learning a temporal sequence. Directly inspired from a hippocampus model [2], this architecture allows an autonomous robot to learn how to imitate a sequence of movements with the correct timing. The results show that the network model is fast, accurate and robust.}, author = {Moga, Sorin and Gaussier, Philippe and Banquet, Jean-Paul }, citeulike-article-id = {2910635}, doi = {10.1007/3-540-44868-3\_26}, journal = {Computational Methods in Neural Modeling}, keywords = {bioinspiration, coding, imitation, learning, neural, robotics, sequence, temporal}, pages = {1036--1037}, posted-at = {2008-06-20 15:53:22}, priority = {3}, title = {Sequence learning using the neural coding}, url = {http://dx.doi.org/10.1007/3-540-44868-3\_26}, year = {2003} }

TY - CHAP ID - citeulike:2910635 L3 - citeulike-article-id:2910635 TI - Sequence learning using the neural coding JF - Computational Methods in Neural Modeling SP - 1036 EP - 1037 N2 - This article introduces a neural network capable of learning a temporal sequence. Directly inspired from a hippocampus model [2], this architecture allows an autonomous robot to learn how to imitate a sequence of movements with the correct timing. The results show that the network model is fast, accurate and robust. KW - bioinspiration KW - coding KW - imitation KW - learning KW - neural KW - robotics KW - sequence KW - temporal AU - Moga, Sorin AU - Gaussier, Philippe AU - Banquet, Jean-Paul PY - 2003/// UR - http://dx.doi.org/10.1007/3-540-44868-3_26 ER -