This function computes the gradient for a one hidden layer network.
computeGrad1(x, y, I, H, weights, f, f_d, m_f)properties of observation
characteristic of observation (zero or one)
numbers of input neurons
numbers of hidden neurons
the weights with that the gradient should be computed
the activation function of the neural network
the derivative of the activation function
the function for the interim value m. It is two times the output of the network minus the observed characteristic.
A Weights class with the gradient parts