[source] # SELU Scaled Exponential Linear Units (SELU) are a self-normalizing activation function based on the [ELU](#elu) activation function. Neuronal activations of SELU networks automatically converge toward zero mean and unit variance, unlike explicitly normalized networks such as those with [Batch Norm](#batch-norm) hidden layers. $$ {\displaystyle SELU = 1.0507 {\begin{cases}1.67326 (e^{x}-1)&{\text{if }}x<0\\x&{\text{if }}x\geq 0\end{cases}}} $$ ## Parameters This actvation function does not have any parameters. ## Example ```php use Rubix\ML\NeuralNet\ActivationFunctions\SELU; $activationFunction = new SELU(); ``` ## References [^1]: G. Klambauer et al. (2017). Self-Normalizing Neural Networks.