Germano C. Vasconcelos

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The reliability of feedforward neural networks with respect to the rejection of patterns not belonging to the deened training classes is investigated. It is shown how networks with diierent activation functions and propagation rules construct the decision regions in the pattern space and, therefore, aaect the network's performance in dealing with spurious(More)
Multilayer perceptron networks (MLP) are investigated with respect to the problem of the detection of spurious patterns. A novel mechanism is proposed based on the ideas of boot-strapping that when incorporated into the standard MLP provides the network with the ability to continuously modifying its responses across the input space. The mechanism makes use(More)
Neural networks and logistic regression have been among the most widely used AI techniques in applications of pattern clussiftiution. MLK~ has been discrlssed about if there is any signzficunt d&erence in between them but much less has been actually done with real-world applications data (large scale) to help settle this mutter, with a few exceptions. This(More)
This paper presents a new method --- the Time-delay Added Evolutionary Forecasting (TAEF) method --- for time series prediction which performs an evolutionary search of the minimum necessary number of dimensions embedded in the problem for determining the characteristic phase space of the time series. The method proposed is inspired in F. Takens theorem and(More)