Can we normalize data to unit variance without distorting the phase?

1. How do you normalize data to unit variance?
2. When should you normalize data?
3. What process normalizes data to mean 0 and variance 1?

How do you normalize data to unit variance?

You can determine the mean of the signal, and just subtract that value from all the entries. That will give you a zero mean result. To get unit variance, determine the standard deviation of the signal, and divide all entries by that value. Save this answer.

When should you normalize data?

Normalization is useful when your data has varying scales and the algorithm you are using does not make assumptions about the distribution of your data, such as k-nearest neighbors and artificial neural networks. Standardization assumes that your data has a Gaussian (bell curve) distribution.

What process normalizes data to mean 0 and variance 1?

What is Normalization? It is a scaling technique method in which data points are shifted and rescaled so that they end up in a range of 0 to 1. It is also known as min-max scaling.