Animating neural network training
Etienne van der Poel, Ian Cloete · Unisa Institutional Repository (University of South Africa) · 1992
In Artificial Neural Network (ANN) simulation it is usually necessary to examine the behaviour of the ANN and detect problems if they occur. However, due to the large volume and high dimensionality of data generated during ANN simulation, interpretation of results is difficult. By using visualisation techniques, such as simple animated faces, problems that occur during the training of a back-propagation neural network can be detected and analyzed. The dynamic behaviour of the network is also better understood when using animation as part of the visualization process.