%0 Journal Article
%4 sid.inpe.br/mtc-m21b/2015/02.02.13.03
%2 sid.inpe.br/mtc-m21b/2015/02.02.13.03.03
%@doi 10.1063/1.44713
%T Neural network model for memory
%D 1992
%9 conference paper
%A Vipin, Meena,
%A Granato, Enzo,
%@affiliation University of Hyderabad
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress
%@electronicmailaddress enzo@las.inpe.br
%B AIP Conference Proceedings
%V 286
%P 336-338
%K Optical computers logic elements interconnects switches, neural networks, General theory and mathematical aspects.
%X We propose a model for memory within the framework of Neural Network which is akin to the realistic memory, in that it tends to forget upon learning more, and has both long-term as well as short-term memories. It has great advantage over the existing models proposed so far by Parisi and Gordon which have only short-term and long-term memories respectively. Our model resorts to learning within bounds like the previous two models, however, the essential difference lies in the reinitialization of the synaptic efficacy after it accumulates up to a preassigned value.
%@language en
%3 Istec 1995.pdf