Search Results - "Mantas, C.J."

Artificial Neural Networks are Zero-Order TSK Fuzzy Systems by Mantas, C.J., Puche, J.M.

“…In this paper, the functional equivalence between the action of a multilayered feed-forward artificial neural network (NN) and the performance of a system…”
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Interpretation of artificial neural networks by means of fuzzy rules by Castro, J.L., Mantas, C.J., Benitez, J.M.

“…This paper presents an extension of the method presented by Benitez et al (1997) for extracting fuzzy rules from an artificial neural network (ANN) that…”
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SEPARATE: a machine learning method based on semi-global partitions by Castro, J.L., Delgado, M., Mantas, C.J.

“…Presents a machine learning method for solving classification and approximation problems. This method uses the divide-and-conquer algorithm design technique…”
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Extraction of fuzzy rules from support vector machines by Castro, J.L., Flores-Hidalgo, L.D., Mantas, C.J., Puche, J.M.

“…The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy…”
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Extraction of similarity based fuzzy rules from artificial neural networks by Mantas, C.J., Puche, J.M., Mantas, J.M.

“…A method to extract a fuzzy rule based system from a trained artificial neural network for classification is presented. The fuzzy system obtained is equivalent…”
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Neural networks with a continuous squashing function in the output are universal approximators by Castro, J.L., Mantas, C.J., Benı́tez, J.M.

“…In 1989 Hornik as well as Funahashi established that multilayer feedforward networks without the squashing function in the output layer are universal…”
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A procedure for improving generalization in classification trees by Mantas, C.J., Mantas Ruiz, J.M., Rojas, F.

“…This article presents a procedure for improving generalization in classification trees. This procedure consists of adjusting the nodes of a tree with the aim…”
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A fuzzy rule-based algorithm to train perceptrons by Castro, J.L., Delgado, M., Mantas, C.J.

“…In this paper, a method to train perceptrons using fuzzy rules is presented. The fuzzy rules linguistically describe how to upgrade the weights as well as to…”
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A fuzzy control based algorithm to train perceptrons by Delgado, M., Mantas, C.J., Pegalajar, M.C.

“…In this paper a method to train perceptrons using a fuzzy controller is presented. When the first layer of a perceptron is trained, the fuzzy rules try for…”
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A neuro-fuzzy approach for feature selection by Benitez, J.M., Castro, J.L., Mantas, C.J., Rojas, F.

“…A method for feature selection based on a combination of artificial neural network and fuzzy techniques is presented. The procedure produces a ranking of…”
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