Sequence learning has a variety of different approaches. We can distinguish two fundamental approaches: general-regularity learning and specific sequence learning. Although some studies suggest that it is possible for a single subsystem underlying both general-regularity and specific-sequence learning, it is proved that relatively independent subsystems may execute the two types of learning more efficiently than a single subsystem. In this paper we propose to implement specific sequence learning in a neural network with no memory and with an implicit representation of time
An Adaptable Boolean Neural Network Performing Specific Sequence Learning / Lauria, F. E.; Prevete, Roberto; Milo, M.. - STAMPA. - 3:(2000), pp. 181-185. (Intervento presentato al convegno International Joint Conference on Neural Networks (IJCNN'00) tenutosi a Como, Italy nel July 24-27, 2000) [10.1109/IJCNN.2000.861402].
An Adaptable Boolean Neural Network Performing Specific Sequence Learning
PREVETE, ROBERTO;
2000
Abstract
Sequence learning has a variety of different approaches. We can distinguish two fundamental approaches: general-regularity learning and specific sequence learning. Although some studies suggest that it is possible for a single subsystem underlying both general-regularity and specific-sequence learning, it is proved that relatively independent subsystems may execute the two types of learning more efficiently than a single subsystem. In this paper we propose to implement specific sequence learning in a neural network with no memory and with an implicit representation of timeI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
