The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networksâ€¦ (More)

The Broyden-Fletcher-Goldfarh-Shanno (BFGS) optimization algorithm usually used for nonlinear least squares is presented and is combined with the modified back propagation algorithm yielding a newâ€¦ (More)

Neural-network techniques, particularly back- propagation algorithms, have been widely used as a tool for discovering a mapping function between a known set of input and output examples. Neuralâ€¦ (More)

The conjugate gradient optimization algorithm usually used for nonlinear least squares is presented and is combined with the modified back propagation algorithm yielding a new fast trainingâ€¦ (More)

In a 'feed forward' algorithm, the slope of the activation function is directly influenced by a parameter referred to as 'gain'. In this paper, the influence of the variation of 'gain' on theâ€¦ (More)