Gradient Descent

A learning algorithm using gradient descent method is not easy to implement in an electronic circuit and has local minimum.

The improved gradient descent algorithm has been used to train the wavelet neural network.

In this method a wavelet neural network model is built, through a gradient descent error algorithm, the network updates its parameters.

BP neural network, as its nature of gradient descent method, is easy to fall into local optimum.

This paper researches the application of the stochastic parallel gradient descent(SPGD)optimization algorithm on the beam cleanup system.

Computer simulations verify the gradient, descent algorithm is effective and feasible.

Gradient-descent algorithm is used to iteratively improve estimate of the head pose.

To test performance, it's compared with gradient descent algorithm, PSO algorithm and QPSO algorithm.

Gradient descent algorithm is an efficient method to train FNN, and it can be realized in batch or incremental manner.

However, BP network with gradient descent has some defects such as low convergence speed, fall in local minima.

The delta rule is based on the idea of gradient descent.

Feed-forward neural networks; Generalization; ability; Gradient descent method; Regularization; Information entropy;

Comparison between GA and gradient descent algorithm in parameter optimization of UPFC fuzzy damping controller

Combined algorithms for training RBF neural networks based on genetic algorithms and gradient descent

An Armijo Stepsize Gradient - descent Algorithm for Optimal Control of Switched Dynamical Systems

Study on Adaptive Fuzzy Control System Based on Gradient Descent Learning Algorithm

Gradient-descent is used to train the weights which make the cost function minimized;

Voltage gradient descent at time to prevent from reverse breakdown

A Fast Learning Method of Fuzzy Systems Based on GA and Gradient Descent Method