Sparsity: ReLU sets negative values to zero, encouraging sparsity in the network's activations. Avoiding Vanishing Gradients: Compared to sigmoid or tanh, ReLU avoids the vanishing gradient problem ...

ReLU_Plus_Plus is a variant of the ReLU function that attempts to mitigate these limitations. It allows adjusting the slope for positive and negative values, which can improve the performance of ...

In words, to compute the value of a hidden node, you multiply each input value times its associated input-to-hidden weight, add the products up, then add the bias value, and then apply the leaky ReLU ...

Motivated by the linearity of the ring VCO's V-to-F characteristics in this paper we present a low power ReLU activation function for pulsed neural network. The proposed rectifier is based-on our ...