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_posts/2025-11-17-d2l_convolutional-modern.md

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@@ -261,13 +261,7 @@ net = nn.Sequential(
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操作:对小批量数据进行均值和方差标准化,再应用可学习的拉伸($\gamma$)和偏移($\beta$)参数
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公式:
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$$
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\mathrm{BN}(\mathbf{x}) = \boldsymbol{\gamma} \odot \frac{\mathbf{x} - \hat{\boldsymbol{\mu}}_\mathcal{B}}{\hat{\boldsymbol{\sigma}}_\mathcal{B}} + \boldsymbol{\beta}
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$$
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其中 $\hat{\boldsymbol{\mu}}_\mathcal{B}$ 为小批量均值,$\hat{\boldsymbol{\sigma}}_\mathcal{B}$ 为小批量标准差(加 $\epsilon$ 防除零)
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公式:$\mathrm{BN}(\mathbf{x}) = \boldsymbol{\gamma} \odot \frac{\mathbf{x} - \hat{\boldsymbol{\mu}}_\mathcal{B}}{\hat{\boldsymbol{\sigma}}_\mathcal{B}} + \boldsymbol{\beta}$
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### 7.5.2. 关键特性
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