gradient descent adaptive learning rate backpropagation

Weight Changes for Learning Mechanisms in Two-Term Back.

IEEE Xplore - Improving the learning rate of back-propagation with.

An Approach to Improve Back-propagation algorithm by Using.
Jan 16, 2013. To prevent this problem occurring, the step of gradient descent is controlled by a parameter called the learning rate.. Owing to the usefulness of two-termBP and the adaptive learning method in learning the. the minimum point where the solution converges by calculating its gradient and back propagation.

gradient descent adaptive learning rate backpropagation

Improving the accuracy of gradient descent back propagation.

Jan 16, 2013. To prevent this problem occurring, the step of gradient descent is controlled by a parameter called the learning rate.. Owing to the usefulness of two-termBP and the adaptive learning method in learning the. the minimum point where the solution converges by calculating its gradient and back propagation.
Feb 7, 2013. Improving the accuracy of gradient descent back propagation algorithm. learning rate, momentum, network topology, activation function and 'gain'. known as 'Gradient Descent Method with Adaptive Momentum (GDAM)' is.
However, by using back propagation (BP) based on gradient descent. In this research, we modified existing back propagation learning algorithm with adaptive gain by adaptively change the momentum coefficient and learning rate.
An Approach to Improve Back-propagation algorithm by Using Adaptive Gain more... For gradient descent algorithm, the learning rate value was 0.3 and the .
The effect of adaptive parameters on the performance of back.
Jan 16, 2013. To prevent this problem occurring, the step of gradient descent is controlled by a parameter called the learning rate.. Owing to the usefulness of two-termBP and the adaptive learning method in learning the. the minimum point where the solution converges by calculating its gradient and back propagation.
Feb 7, 2013. Improving the accuracy of gradient descent back propagation algorithm. learning rate, momentum, network topology, activation function and 'gain'. known as 'Gradient Descent Method with Adaptive Momentum (GDAM)' is.
However, by using back propagation (BP) based on gradient descent. In this research, we modified existing back propagation learning algorithm with adaptive gain by adaptively change the momentum coefficient and learning rate.
An Approach to Improve Back-propagation algorithm by Using Adaptive Gain more... For gradient descent algorithm, the learning rate value was 0.3 and the .
With standard steepest descent, the learning rate is held constant throughout. Backpropagation training with an adaptive learning rate is implemented with the . Gradient 2.6397/ 1e-06 TRAINGDA, Epoch 44/300, MSE 7.47952e-06/1e-05.

The Effect of Adaptive Momentum in Improving the Accuracy of.

IEEE Xplore - A direct adaptive method for faster backpropagation.
Jan 16, 2013. To prevent this problem occurring, the step of gradient descent is controlled by a parameter called the learning rate.. Owing to the usefulness of two-termBP and the adaptive learning method in learning the. the minimum point where the solution converges by calculating its gradient and back propagation.
Feb 7, 2013. Improving the accuracy of gradient descent back propagation algorithm. learning rate, momentum, network topology, activation function and 'gain'. known as 'Gradient Descent Method with Adaptive Momentum (GDAM)' is.
However, by using back propagation (BP) based on gradient descent. In this research, we modified existing back propagation learning algorithm with adaptive gain by adaptively change the momentum coefficient and learning rate.
An Approach to Improve Back-propagation algorithm by Using Adaptive Gain more... For gradient descent algorithm, the learning rate value was 0.3 and the .
With standard steepest descent, the learning rate is held constant throughout. Backpropagation training with an adaptive learning rate is implemented with the . Gradient 2.6397/ 1e-06 TRAINGDA, Epoch 44/300, MSE 7.47952e-06/1e-05.
Nov 8, 2012. The Back Propagation algorithm or its variation on Multilayered Feedforward. method known as Back Propagation Gradient Descent with Adaptive Gain, Adaptive Momentum and Adaptive Learning Rate (BPGD-AGAMAL).
Variable Learning Rate (traingda, traingdx).