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Neural Networks Examples

The following examples demonstrate how Neural Networks can be used to find relationships among data. Different neural network models are trained using a collection of data from a given source and, after successful training, the neural networks are used to perform classification or prediction of new data from the same or similar sources.

Hopfield Networks (Interactive)
Illustrates the use of Hopfield networks for classification and for restoring distorted patterns using Neural Networks and webMathematica

Classification of Paper Quality
Applies different types of neural networks to classify the data from a hybrid gas array sensor, an electronic nose, recording the odor from different cardboard paper samples

Prediction of Currency Exchange Rate
Compares how linear and nonlinear models, based on feedforward and radial basis function networks, predict daily currency exchange rates using the rates from previous days

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