A jumpnet includes two memory storage
systems: a processing network that employs
superimpositional storage and a control
network that recodes input patterns into
minimally overlapping hidden patterns. By
creating temporary, input-specific changes in
the weights of the processing network, the
control network causes the processing network to
"jvimp" to the region of its weight space that is
most appropriate for a particular input pattern.
Simulation results demonstrate that jumpnets
exhibit only moderate levels of interference
while retaining the computational advantages
of superimpositional memory.
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