The nlogistic-sigmoid function

The variants of sigmoid functions used in artificial neural networks are, by definition, limited by vanishing gradients. Defining the sigmoid function to become n-times repeated over a finite input-output map can significantly reduce the presence of this limitation. This function mapping as proposed in this paper is the nlogistic-sigmoid function.