Solution for XOR Problem with Neural Networks Using Google Colab and MATLAB / Simulink

To find solution for XOR problem we are considering two widely used software that is being relied on by many software developers for their work. The first software is Google Colab tool which can be used to implement ANN programs by coding the neural network using python. This tool is reliable since it supports python language for its implementation. The other major reason is that we can use GPU and TPU processors for the computation process of the neural network. The major advantage of this is that for complex Neural Networks instead of using CPU present in the user’s system we can use those two processors through online mode without purchasing such processors for our computation. The next software that can be used for implementing ANN is Matlab Simulink. This software is used for highly calculative and computational tasks such as Control System, Deep Learning, Machine Learning, Digital Signal Processing and many more. Matlab is highly efficient and easy to code and use when compared to any other software. This is because Matlab stores data in the form of matrices and computes them in this fashion. Matlab in collaboration with Simulink can be used to manually model the Neural Network without the need of any code or knowledge of any coding language. Since Simulink is integrated with Matlab we can also code the Neural Network in Matlab and obtain its mathematically equivalent model in Simulink. Also, Matlab has a dedicated tool in its library to implement neural network called NN tool. Using this tool, we can directly add the data for input, desired output, or target. After inserting the required data, we can train the network with the given dataset and receive appropriate graph’s which will be helpful in analyzing the data. Once the Neural Network is trained, we can test the network through this tool and verify the obtained results.