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Recurrent neural network design for temporal sequence learning

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2 Author(s)
Kwan, H.K. ; Dept. of Electr. & Comput. Eng., Windsor Univ., Ont., Canada ; Yan, J.

Presents two designs of a recurrent neural network with 1st and 2nd order self-feedback at the hidden layer. The first design is based on a gradient descent algorithm and the second design is based on a genetic algorithm (GA). The simulation results of the single hidden layer network and those of a single hidden layer feedforward neural network for learning 50 commands of up to 3 words and 24 phone numbers of 10 digits are presented. Results indicate that the GA-based dynamic recurrent neural network is best in both convergence and error performance

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Circuits and Systems, 2000. Proceedings of the 43rd IEEE Midwest Symposium on  (Volume:2 )

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