Implementation of XOR Gate Using Multi-Layer Perceptron/ Error Back Propagation


1. The aim is to implement MLP Algorithms on Ex-OR Gate.
2. Firstly, Select the algorithm which is to be implemented i.e. FeedForward or Error Back Propagation.
3. Enter the weights, bias, threshold values.
4. Enter the number of iterations (Epochs) and the learning rate of the system ( Only in case of EBPMLP ).
5. Depending on the algorithm chosen and the input values are given the following things could be observed:-

a. Start the simulation.
b. Simulation of the model will be generated.
c. Stepwise calculation of different intermediate and final outputs will be visible during the real-time simulation.
d. Moreover, the graph will be plotted according to the weights and threshold values are chosen so as to understand how the clustering of the different group takes place.

6. After understanding the whole simulation for 1 input, then Apply the next set of inputs.
7. Successively the changed weight and bias values will be shown for a clear understanding of EBPMLP.
8. If proper inputs of weight and bias are not provided then a hint having all the appropriate input values is also given to observe the correct simulation of the algorithm.
9. Later, Answer the Post Test questions to ascertain the correctness of your understanding.

Note:The simulation for error back propagation may hang if the number of iterations entered is greater than or equal to 100000. The answer will come, albeit with a minimal delay

* Hints to get correct output are provided in the Post Test section.