Vol. 2, Issue 8, Part C (2016)

Abstract
Neural Networks are relatively crude electronic models based on the neural structure of the brain. The brain basically learns from experience. It is natural proof that some problems that are beyond the scope of current computers are indeed solvable by small energy efficient packages. In this paper we propose the fundamentals of neural network topologies, activation function and learning algorithms based on the flow of information in bi-direction or uni-directions. We outline the main features of a number of popular neural networks and provide an overview on their topologies and their learning capabilities.