In this paper, a neural network is trained and validated using a low end and inexpensive microcontroller. The well-known backpropagation algorithm is implemented to train a neural network model. Both the training and the validation parts are shown through an alphanumeric liquid crystal display. A chemical process was chosen as a realistic nonlinear system to demonstrate the feasibility, and the performance of the results found using the microcontroller. A comparison was made between the microcontroller and the computer results.
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