brainpy.inputs.ou_process#
- brainpy.inputs.ou_process(mean, sigma, tau, duration, dt=None, n=1, t_start=0.0, t_end=None, seed=None)[source]#
Ornstein–Uhlenbeck input.
\[dX = (mu - X)/\tau * dt + \sigma*dW\]- Parameters:
mean (float) – Drift of the OU process.
sigma (float) – Standard deviation of the Wiener process, i.e. strength of the noise.
tau (float) – Timescale of the OU process, in ms.
duration (float) – The input duration.
dt (float) – The numerical precision.
n (int) – The variable number.
t_start (float) – The start time.
t_end (float) – The end time.
seed (optional, int) – The random seed.