brainpy.inputs.ou_process

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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.

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