We study three kinds of compactness in some variants of G"{o}del logic: compactness,entailment compactness, and approximate entailment compactness.For countable first-order underlying language we use the Henkinconstruction to prove the compactness property of extensions offirst-order g logic enriched by nullary connective or the Baaz'sprojection connective. In the case of uncountable first-orde...

In this paper, the well-known Egoroff’s theorem in classical measure theory is established on monotone non-additive measure spaces. Taylor’s theorem, which concerns almost everywhere convergence of measurable function sequence in classical measure theory, is also generalized. The converse problem of the theorems are discussed, and a necessary and sufficient condition for the Egoroff’s theorem i...

We present some model theoretic results for Lukasiewicz predicate logic by using the methods of continuous model theory developed by Chang and Keisler. We prove compactness theorem with respect to the class of all structures taking values in the Lukasiewicz BL-algebra. We also prove some appropriate preservation theorems concerning universal and inductive theories. Finally, Skolemization and Mo...

Some known compactness notions and separation axioms already given in Chang-fuzzy topological spaces are extended to a more general context of categories where I -topological spaces on arbitrary I -sets are de3ned. The invariance under morphisms in these categories and the usual hereditary conditions of the considered topological properties in such a context are investigated. c © 2002 Elsevier ...

This paper presents a robust technique for Content Based Image Retrieval (CBIR) using salient points of an image. The salient points are extracted from different levels of the unsegmented image. Local contrast information at different resolution is embedded along with shape information. Fuzzy compactness vector is computed from the signature obtained at different thresholds. The resemblance of ...

Multi-objective evolutionary algorithms represent an effective tool to improve the accuracyinterpretability trade-off of fuzzy rule-based classification systems. To this aim, a tuning process and a rule selection process can be combined to obtain a set of solutions with different trade-offs between the accuracy and the compactness of models. Nevertheless, an initial model needs to be defined, i...