Artificial neural networks (ANNs) are systems that are constructed to use some organizational principles resembling those of the human brain. They are information processing systems that demonstrate the ability to learn, recall, and generalize from training patterns or data. ANNs are good at tasks such as pattern matching and classification, data clustering, and forecasting.
Neuro3 software uses the backpropagation neural network (BPN), the most widely used feedforward neural network system. The term backpropagation refers to the training method by which the weights of the network connection are adjusted. The calculations procedure is feedforward, from input layer through hidden layers to output layer. During training, the calculated outputs are compared with the desired values, and then the errors are backpropagated to correct all weight factors.
All Training factors are defined by the users, including
Network and training parameters are stored in scenario files and on projects spreadsheets which may be copied and pasted to other spreadsheet programs.
