# PELU activation: how does it work, and how to implement?

I have encountered PELU (Parametric Exponential Linear Unit) in the literature, but I can't find practical applications of it.

Moreover, I have some questions about how it works:

• Are its parameters learned, or are they hyperparameters?

• Is a Keras Custom layer required for a TensorFlow implementation?

• In the original paper, it was applied to convolutional models only. Could you share links to applications outside Computer Vision?

• Computational burden aside, is its performance proven (outside original paper) to be superior to more classical activations from the ReLU family?

tf.cond(h, lambda:c*h, lambda:a(tf.exp(h/b)-1))