文件名称:microcontroller_neural_network
下载
别用迅雷、360浏览器下载。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
介绍说明－－下载内容均来自于网络，请自行研究使用
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.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
microcontroller_neural_network.c