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Point processes.
Here ' + ' means the superposition of two point processes.
Point processes were employed to model the spike trains.
Modeling and analysis techniques involving spatial point processes are reviewed.
For some basic properties of point processes, see [2], for example.
The result for binomial point processes will follow from Theorem 1.6 and the following result.
Time is discretized and the point processes approximated by 0 1 time series.
Many authors further studied the asymptotic behavior of exceedance point processes under different conditions.
The inputs that will be considered in this paper behave as Poisson random point processes.
Spatial point processes are the common approach to model and analyze random point patterns.
We model the output spike trains of single neurons by stochastic point processes.
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