A novel backpropagation learning algorithm for a particular class of dynamic neural networks in which some units have a local feedback is proposed. Hence these networks can be trained to respond to sequences of input patterns. This algorithm has the same order of space and time requirements as backpropagation applied to feedforward networks. The authors present experimental results and comparisons with a speech recognition problem.
Bengio, Y., De, M., Gori, M. (1989). BPS: A learning algorithm for capturing the dynamic nature of speech. In Proceedings of the IEEE-IJCNN 1989 International Conference on Neural Networks (pp.417-423). IEEE.
BPS: A learning algorithm for capturing the dynamic nature of speech
Gori M.
1989-01-01
Abstract
A novel backpropagation learning algorithm for a particular class of dynamic neural networks in which some units have a local feedback is proposed. Hence these networks can be trained to respond to sequences of input patterns. This algorithm has the same order of space and time requirements as backpropagation applied to feedforward networks. The authors present experimental results and comparisons with a speech recognition problem.
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https://hdl.handle.net/11365/33007
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