Recall of old and recent information

dc.contributor.author Srivastava, Vipin
dc.contributor.author Vipin, Meena
dc.contributor.author Granato, Enzo
dc.date.accessioned 2022-03-26T23:44:07Z
dc.date.available 2022-03-26T23:44:07Z
dc.date.issued 1998-01-01
dc.description.abstract A neural network model for 'forgetting upon learning' is developed in such a way that old information can also be evoked. A new synaptic clipping scheme coupled with selective reinforcement of information is introduced that mimics the learning and memory functions of the 'limbic system' in the brain. The model thus enables both long-term (old) and short-term (recent) memories to exist concurrently, without one affecting the other, as one expects in a realistic situation. © 1998 IOP Publishing Ltd.
dc.identifier.citation Network: Computation in Neural Systems. v.9(2)
dc.identifier.issn 0954898X
dc.identifier.uri 10.1088/0954-898X_9_2_001
dc.identifier.uri https://www.tandfonline.com/doi/full/10.1088/0954-898X_9_2_001
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/2341
dc.title Recall of old and recent information
dc.type Journal. Article
dspace.entity.type
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