types.core.NoiseVector

types.core.NoiseVector

Noise/disturbance vector w ∈ ℝⁿʷ (stochastic systems only).

For continuous SDEs: Brownian motion increment dW For discrete stochastic: Standard normal w[k] ~ N(0, I)

Shapes: - Single sample: (nw,) - Batched samples: (batch, nw) - Noise sequence: (n_steps, nw)

Examples

>>> # Standard normal noise
>>> w: NoiseVector = np.random.randn(2)
>>> 
>>> # Brownian increment (continuous)
>>> dW: NoiseVector = np.random.randn(2) * np.sqrt(dt)
>>> 
>>> # Discrete-time IID noise
>>> w_k: NoiseVector = np.random.randn(2)  # w[k] ~ N(0, I)

# types.core.NoiseVector { #cdesym.types.core.NoiseVector }

`types.core.NoiseVector`

Noise/disturbance vector w ∈ ℝⁿʷ (stochastic systems only).

For continuous SDEs: Brownian motion increment dW
For discrete stochastic: Standard normal w[k] ~ N(0, I)

Shapes:
- Single sample: (nw,)
- Batched samples: (batch, nw)
- Noise sequence: (n_steps, nw)

## Examples {.doc-section .doc-section-examples}

```python
>>> # Standard normal noise
>>> w: NoiseVector = np.random.randn(2)
>>> 
>>> # Brownian increment (continuous)
>>> dW: NoiseVector = np.random.randn(2) * np.sqrt(dt)
>>> 
>>> # Discrete-time IID noise
>>> w_k: NoiseVector = np.random.randn(2)  # w[k] ~ N(0, I)
```