Smart neural nets for fast learning

We introduce what we call the ´smart neural nets´ for fast and well behaved learning. The smart neural nets are formed by completely avoiding the use of the sigmoid nonlinear function driven conventional neurons that are used to construct the neural nets, and by re-designing the neurons appropriately. To develop the smart neural nets, we introduce what we call the ´smart neurons´. The smart neural nets are constructed by forming layers of smart neurons, and interconnecting the adjacent layers. Like the conventional neural nets, the smart neural nets are trained by using the regular innovation backpropagation learning algorithm. We compare the performance of the smart neural nets against the conventional neural nets toward the regular innovation backpropagation learning using the implementation of the two-input exclusive-OR gate.<>