batch_normalization

weighted sum of outputs from the previous layer

gamma

beta

the mean of the input neurons. If NULL, it will be caluclated in the function.

the variance of the input nerurons. If NULL, it will be calcualted in the function.

sigma_2

a constant added to the variance for numerical stability

epsilon


This function normalizes the distribution of inputs to hidden layers in
a neural network


An implementation of deep neural network with rectifier linear units trained
with stochastic gradient descent method and batch normalization. A combination of these methods have
achieved state-of-the-art performance in ImageNet classification by overcoming the gradient saturation
problem experienced by many deep architecture neural network models in the past. In addition,
batch normalization and dropout are implemented as a means of regularization. The deeplearning package is
inspired by the darch package and uses its class DArch.

batch_normalization: Batch Normalization Function that normalizes the input before applying non-linearity

Description

Usage

Arguments

References

See Also