matlab nomalization,Batch normalization layer

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Algorithms

The batch normalization operation normalizes the elements

xi of the input by first calculating the mean

μB and variance

σB2 over the

spatial, time, and observation dimensions for each channel independently. Then, it

calculates the normalized activations as

xi^=xi−μBσB2+ϵ,

where ϵ is a constant that improves numerical

stability when the variance is very small.

To allow for the possibility that inputs with zero mean and unit variance are not optimal for

the operations that follow batch normalization, the batch normalization operation further

shifts and scales the activations using the transformation

yi=γx^i+β,

where the offset β and scale factor

γ are learnable parameters that are updated during network

training.

To make predictions with the network after training, batch norma

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