神经网络不同激活函数比较--读《Understanding the difficulty of training deep feedforward neural networks》
转载：https://ziyubiti.github.io/2016/11/01/actfunpaper/ 这篇论文比较了不同激活函数的中间各隐层输出值分布、梯度值分布、测试准确度等，从上图看出，至少在mnist和cifar10测试集下，看起来tanh和softsign都要好于sigmoid。
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相关文章
- 1. Xavier——Understanding the difficulty of training deep feedforward neural networks
- 2. 【Deep Learning】笔记：Understanding the difficulty of training deep feedforward neural networks
- 3. 论文解析-《Understanding the difficulty of training deep feedforward neural networks》
- 4. Paper之DL之BP：《Understanding the difficulty of training deep feedforward neural networks》
- 5. 神经网络剖析激活函数优缺点（Undetanding the difficulty of training deep feedforward neural networks）
- 6. [论文笔记] [2010] Understanding the Difficulty of Training Deep Feedforward Neural Networks
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- 9. 人工神经网络之激活函数 -Sigmoid函数
- 10. 人工神经网络之激活函数 -tanh函数