Error Backpropagation Method in Omnidirectional Neural Network Using Optimal Learning Rate

摘要

The present invention optimally obtains the learning rate of the error backpropagation algorithm to improve the learning speed of the error backpropagation algorithm. The present invention relates to an error back propagation learning method of an omnidirectional neural network using an optimal learning rate composed of learning rates. In particular, an optimal learning rate of output layer weights is calculated by minimizing the error of the output layer while the middle layer neurons are fixed. Calculate the optimal learning rate of the output layer weights based on the calculated learning rate, calculate the optimal learning rate of the output layer weights based on the calculated learning rate, change the output layer weights based on the calculated learning rate, and change the middle layer weights while fixing the changed output layer weights. The learning rate is calculated by calculating the optimal learning rate for each learning pattern and the optimum learning rate for each middle layer neuron, and by using the learning rate calculated by changing the middle weight. .