1.
Neural Netw
; 16(5-6): 683-9, 2003.
Article
in English
| MEDLINE
| ID: mdl-12850023
ABSTRACT
We illustrate the ability of a fixed-weight neural network, trained with Kalman filter methods, to perform tasks that are usually entrusted to an explicitly adaptive system. Following a simple example, we demonstrate that such a network can be trained to exhibit input-output behavior that depends on which of two conditioning tasks was performed a substantial number of time steps in the past. This behavior can also be made to survive an intervening interference task.