# Input layer batch normalization

If we apply batch normalization to the input layer, is the resulting (trained) network equivalent to the same network without batch normalization with input standardization wrt biased mean and variance estimators?

Of course, the estimates vary during training, so the ending weights won't be the same, but if my intuition is correct then would it be reasonable to use a batch norm layer instead of standardization for pre-processing?