Neural Network Task Three

The third task was to test the RBF network with the full sets of character using medium resolution data, that is, 0 to 9, A to Z and a space character. Therefore there were a total of 37 characters. A RBF network was created with 24 input neurons, 50 prototype neurons and 37 output neurons. The network takes a longer time to train and it learns for 80,000 iteration before the RMS error converges. The network was then improved by increasing the number of prototype neurons. A total of four different number of prototype neurons(50, 70, 100 and 180) were used to run the networks and all results are recorded. As the output classes are larger, more prototype neurons were to be used for clustering.