说明：  Using MATLAB tools for MLP NNs (e.g., newff, …), design a two-layer feed-forward neural network as a classifier to categorize the input geometric shapes. - The snapshot and bitmap of shapes are given: - Training shapes: shkt.bmp - Training patterns: trn.txt (each shape is in a 125*140 matrix) - Test shapes: shks.bmp - Test patterns: tsn.txt (each shape is in a 125*140 matrix) - Since the dimension of inputs is too high (17500-dimensional), it is not possible to apply them directly to the net. So, … . - Try the number of hidden neurons to be at least. - Do training of NN until all training patterns are truly classified. - To examine the generalization ability of your NN after training, a) Apply it to the test patterns and report the accuracies. b) Add p noise (p=5, 10, …, 75) to the training shapes (only degrade the black pixels of the shapes) and report in a plot the accuracy versus p.