Table 1 Procedures of batch normalization
From: A robust modulation classification method using convolutional neural networks
| Input: B, γ, β | |
|---|---|
| Output: y={y1,y2,...,ym} | |
| 1. | Calculate the mean and variance value of B: |
| \(\mu _{B}=\frac {1}{m}\sum _{i=1}^{m}x_{i},\) | |
| \(\sigma _{B}^{2}=\frac {1}{m}\sum _{i=1}^{m}(x_{i}-\mu _{B})^{2}\) | |
| 2. | Normalize |
| \(\hat {x_{i}}=\frac {x_{i}-\mu _{B}}{\sqrt {\sigma _{B}^{2}+\epsilon }}\) | |
| 3. | Scale and shift |
| \(y_{i}=\gamma \hat {x_{i}}+\beta \) | |
