Abstract. This paper introduces an approximate fuzzy representation to FuzzyUCS, a Michigan-style Learning Fuzzy-Classifier System that evolves linguistic fuzzy rules, and studies ...
Albert Orriols-Puig, Jorge Casillas, Ester Bernad&...
We consider trellis-based algorithms for data estimation in digital communication systems. We present a general framework which includes approximate Viterbi algorithms like the M-...
A novel method for the robust identification of interpretable fuzzy models, based on the criterion that identification errors are least sensitive to data uncertainties and modelli...
The logistic regression model is used to predict a binary response variable in terms of a set of explicative ones. The estimation of the model parameters is not too accurate and t...
Ana M. Aguilera, Manuel Escabias, Mariano J. Valde...
Applying the programming-language concept of continuations, we propose a new multimodal analysis of quantification in Type Logical Grammar. Our approach naturally gives rise to a n...