diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -208,4 +208,36 @@ graph TB
     output --> delay2[z^-1] --> multATT2["*(1 - AT)"] & multRTT2["*(1 - RT)"]
 
     plus3 & plus4 --> output
-```
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+```
+
+## Average filter
+
+### Function signature
+
+```python
+def avg(rms: torch.Tensor, avg_coef: Union[torch.Tensor, float]):
+    """Compute the running average of a signal.
+
+    Args:
+        rms (torch.Tensor): Input signal.
+        avg_coef (torch.Tensor): Coefficient for the average RMS.
+
+    Shape:
+        - rms: :math:`(B, T)` where :math:`B` is the batch size and :math:`T` is the number of samples.
+        - avg_coef: :math:`(B,)` or a scalar.
+
+    """
+```
+
+### Equations
+
+$$
+\hat{x}_{\rm rms}[n] = \alpha_{\rm avg} x_{\rm rms}[n] + (1 - \alpha_{\rm avg}) \hat{x}_{\rm rms}[n-1]
+$$
+
+## TODO
+
+- [x] CUDA acceleration in Numba
+- [ ] PyTorch CPP extension
+- [ ] Native CUDA extension
+- [ ] Examples
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