Adaptive neural oscillator using continuous-time back-propagation learning

[1]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[2]  J J Hopfield,et al.  Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[3]  W. O. Friesen,et al.  Neuronal generation of the leech swimming movement. , 1978, Science.

[4]  Masao Ito,et al.  Climbing fibre induced depression of both mossy fibre responsiveness and glutamate sensitivity of cerebellar Purkinje cells , 1982, The Journal of physiology.

[5]  Pineda,et al.  Generalization of back-propagation to recurrent neural networks. , 1987, Physical review letters.

[6]  Bernard Widrow,et al.  Adaptive Signal Processing , 1985 .

[7]  Shun-ichi Amari,et al.  Statistical neurodynamics of associative memory , 1988, Neural Networks.

[8]  G. Allen,et al.  Cerebrocerebellar communication systems. , 1974, Physiological reviews.

[9]  S. Grillner Locomotion in vertebrates: central mechanisms and reflex interaction. , 1975, Physiological reviews.

[10]  A. Luria Higher Cortical Functions in Man , 1980, Springer US.

[11]  Fernando J. Pineda,et al.  GENERALIZATION OF BACKPROPAGATION TO RECURRENT AND HIGH-ORDER NETWORKS. , 1987 .

[12]  Allen I. Selverston,et al.  A consideration of invertebrate central pattern generators as computational data bases , 1988, Neural Networks.

[13]  Bernard Widrow,et al.  Neural nets for adaptive filtering and adaptive pattern recognition , 1988, Computer.

[14]  Mitsuo Kawato,et al.  Feedback-error-learning neural network for trajectory control of a robotic manipulator , 1988, Neural Networks.