文件名称:microcontroller_neural_network
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This a simple program to calculate the output of artificial neural network (ANN) using microcontroller ATMega 32.
Assume that the neural architecture is : 2 hidden layers with 4 and 2 neurons
respectively and 1 layer output with 1 neuron.This program explains the step how to compute the ANN in off-line mode.Means
the weights and biases are already exist (microcontroller is not doing the learning steps). These parameters are produced using MATLAB. Therefore, we have already made the appropriate architecture using MATLAB. The tansig function is use in both of hidden layer.
Finally, the neural output will be displayed on LCD port C.-This is a simple program to calculate the output of artificial neural network (ANN) using microcontroller ATMega 32.
Assume that the neural architecture is : 2 hidden layers with 4 and 2 neurons
respectively and 1 layer output with 1 neuron.This program explains the step how to compute the ANN in off-line mode.Means
the weights and biases are already exist (microcontroller is not doing the learning steps). These parameters are produced using MATLAB. Therefore, we have already made the appropriate architecture using MATLAB. The tansig function is use in both of hidden layer.
Finally, the neural output will be displayed on LCD port C.
Assume that the neural architecture is : 2 hidden layers with 4 and 2 neurons
respectively and 1 layer output with 1 neuron.This program explains the step how to compute the ANN in off-line mode.Means
the weights and biases are already exist (microcontroller is not doing the learning steps). These parameters are produced using MATLAB. Therefore, we have already made the appropriate architecture using MATLAB. The tansig function is use in both of hidden layer.
Finally, the neural output will be displayed on LCD port C.-This is a simple program to calculate the output of artificial neural network (ANN) using microcontroller ATMega 32.
Assume that the neural architecture is : 2 hidden layers with 4 and 2 neurons
respectively and 1 layer output with 1 neuron.This program explains the step how to compute the ANN in off-line mode.Means
the weights and biases are already exist (microcontroller is not doing the learning steps). These parameters are produced using MATLAB. Therefore, we have already made the appropriate architecture using MATLAB. The tansig function is use in both of hidden layer.
Finally, the neural output will be displayed on LCD port C.
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microcontroller_neural_network.c