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The aim of this section is to illustrate the computational
abilities of our system. The reproducibility of these simulations
has been checked on several networks.
For sake of simplicity, we have performed learning on
elementary input sequences. Elementary means that only one
neuron is stimulated on the primary layer at a given time. The
input sparsity is thus equal to
. This choice
helps to simplify notation and concentrates our attention on the
temporal behavior of our system. A temporal input sequence is
described by a vector containing indices of neurons
, so that
,...,
. The length of the sequence is
. This sequence describes a periodic input signal of period
, which is repeatedly presented, between
and
(
):
,
,
if
,
and
elsewhere.
Subsections
Dauce Emmanuel
2003-04-08