Parameterized Exponential Linear Units, or PELU, is an activation function for neural networks. It involves learning a parameterization of ELU in order to learn the proper activation shape at each layer in a CNN.
The PELU has two additional parameters over the ELU:
$$ f\left(x\right) = cx \text{ if } x > 0 $$ $$ f\left(x\right) = \alpha\exp^{\frac{x}{b}}  1 \text{ if } x \leq 0 $$
Where $a$, $b$, and $c > 0$. Here $c$ causes a change in the slope in the positive quadrant, $b$ controls the scale of the exponential decay, and $\alpha$ controls the saturation in the negative quadrant.
Source: Activation Functions
Source: Parametric Exponential Linear Unit for Deep Convolutional Neural NetworksPaper  Code  Results  Date  Stars 

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