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Conditioned adaptive behavior from Kalman filter trained recurrent networks

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3 Author(s)
Feldkamp, L.A. ; Res. & Adv. Eng., Ford Motor Co., Dearborn, MI, USA ; Prokhorov, D.V. ; Feldkamp, T.M.

We demonstrate that a fixed-weight neural network can be trained with Kalman filter methods to exhibit input-output behavior that depends on which of two conditioning tasks had been performed a substantial number of time steps in the past. This behavior can also be made to survive an intervening interference task.

Published in:

Neural Networks, 2003. Proceedings of the International Joint Conference on  (Volume:4 )

Date of Conference:

20-24 July 2003