ZScoreNormalize

class torch_ecg.preprocessors.ZScoreNormalize(mean: Real | Iterable[Real] = 0.0, std: Real | Iterable[Real] = 1.0, per_channel: bool = False, inplace: bool = True, **kwargs: Any)[source]

Bases: Normalize

Z-score normalization.

Z-score normalization is defined as

\[\left(\frac{sig - \operatorname{mean}(sig)}{\operatorname{std}(sig)}\right) \cdot s + m\]
Parameters:

  • mean (numbers.Real or array_like, default 0.0) – Mean value of the normalized signal, or mean values for each lead of the normalized signal.

  • std (numbers.Real or array_like, default 1.0) – Standard deviation of the normalized signal, or standard deviations for each lead of the normalized signal.

  • per_channel (bool, default False) – Whether to perform the normalization per channel.

  • inplace (bool, default True) – Whether to perform the normalization in-place.