The Poisson distribution is used to get the (interval, and hence) times at which simulated radiation effects occur for a pre-determined, fixed duration window. In this case, the computation first computes the actual unradiated simulation duration, and then uses this to get the window length of the Poisson distribution. The Poisson distribution is determined by the properties:
random seed
lambda as the frequency of effect occurrence. (radiation events per window duration).
Window duration, the number of timesteps for which the simulation is expected to run.
At those interval times, a uniform distribution is used to select which neurons are affected at such a timestep.
Understanding Discrete Uniform distribution.
The uniform distribtuion is only defined by the:
Length of the input list (nr of neurons).
Randomseed+actual/current timestep.
Next, the amplitude of the radiation effect is selected for each of those neurons is selected using a Gaussian distribution.
Ideally change this before calling the
in
apply_synapse_weight_increase_rad(
Understanding Poission
The Poisson distribution is used to get the (interval, and hence) times at which simulated radiation effects occur for a pre-determined, fixed duration window. In this case, the computation first computes the actual unradiated simulation duration, and then uses this to get the window length of the Poisson distribution. The Poisson distribution is determined by the properties:
Understanding Discrete Uniform distribution.
The uniform distribtuion is only defined by the:
Next, the amplitude of the radiation effect is selected for each of those neurons is selected using a Gaussian distribution.
Understanding Gaussian distribution
The Gaussian distribution is defined by: