@Article{VipinGran:1992:NeNeMo,
               author = "Vipin, Meena and Granato, Enzo",
          affiliation = "{University of Hyderabad} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Neural network model for memory",
              journal = "AIP Conference Proceedings",
                 year = "1992",
               volume = "286",
                pages = "336--338",
             keywords = "Optical computers logic elements interconnects switches, neural 
                         networks, General theory and mathematical aspects.",
             abstract = "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.",
                  doi = "10.1063/1.44713",
                  url = "http://dx.doi.org/10.1063/1.44713",
             language = "en",
           targetfile = "Istec 1995.pdf",
        urlaccessdate = "12 maio 2024"
}