# Command: ppd_sup_generator

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Name:

    ppd_sup_generator - simulate the superimposed spike train of a population
      of Poisson processes
      with dead time.

Description:

      The ppd_sup_generator generator simulates the pooled spike train of a
      population of neurons firing independently with Poisson process with dead
      time statistics.
      The rate parameter can also be sine-modulated. The generator does not
      initialize to equilibrium in this case, initial transients might occur.

Parameters:

      The following parameters appear in the element's status dictionary:

      rate	 double	- mean firing rate of the component processes,
      default: 0 s^-1
      dead_time	 double	- minimal time between two spikes of the component
      processes, default: 0 ms
      n_proc	 long  	- number of superimposed independent component
      processes, default: 1
      frequency	 double	- rate modulation frequency, default: 0 Hz
      relative_amplitude  double	- relative rate modulation amplitude, default: 0

Remarks:

      The generator has been published in Deger, Helias, Boucsein, Rotter (2011)
      Statistical properties of superimposed stationary spike trains,
      Journal of Computational Neuroscience.
      URL: http://www.springerlink.com/content/u75211r381p08301/
      DOI: 10.1007/s10827-011-0362-8

      Authors:
      June 2009, Moritz Deger, Moritz Helias

SeeAlso:

- gamma_sup_generator
- poisson_generator_ps
- spike_generator
- Device
- StimulatingDevice

Source:

    /opt/conda/conda-bld/nest_1524088722951/work/nest-2.14.0/models/ppd_sup_generator.h

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