Neural Network Task Two

The second task I have performed was to compare the networks that were tested with different resolution of data. The data set used was the same as the previous, which was from A to J. In the previous task, the data file used is of low resolution, that is, a total of 11 scans per character. For this task, I was using medium resolution data (24 scans) and high resolution data (47 scans) to run the network. It was found out from the previous task that the RBF network with 50 prototype neurons performs slightly better than the MLP network and therefore RBF was used here. The setting for the RBF network was exactly the same as the previous one with 50 prototype neurons except that for the number of input neurons have to be changed to 24 neurons for medium resolution and 47 neurons for high resolution. The network was trained for 20,000 iteration for each resolution before the RMS error converges. The scoring method used was also same as the previous and all results are recorded for both medium and high resolution data.