ANN Algorithm

Artificial neural networks (ANN) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Such systems "learn" to perform tasks by considering examples, generally without being programmed with task-specific rules.  The history of artificial neural networks (ANN) began with Warren McCulloch and Walter Pitts (1943) who created a computational model for neural networks based on algorithms called threshold logic. A key trigger for renewed interest in neural networks and learning was Werbos's (1975) backpropagation algorithm that enabled practical training of multi-layer networks. Backpropagation distributed the error term back up through the layers, by modifying the weights at each node.

ANN source code, pseudocode and analysis