The Simpliied Adaptive Resonance Theory (SART) class of networks is proposed to handle problems encountered in Adaptive Resonance Theory 1 (ART 1)-based algorithms when detection of binary and analog patterns is performed. The basic idea of SART is to substitute ART 1-based \unidirectional" (asymmetric) activation and match functions with \bidirectional" (symmetric) function pairs. This substit...

In this paper, the concept of a fuzzy soft mapping on a fuzzy soft set is introduced and the study of fixed points of such mappings is initiated.

In this paper the concept of soft fuzzy B disconnected space is introduced and studied. In particular, soft fuzzy B disconnectedness via dimension theory is established.

Real world applications are dealing now with a huge amount of data, especially in the area high dimensional features. In this article, we depict simply*upper, simply*lower continuous, get several characteristics and other properties respect to upper lower simply*-continuous soft multi-functions. We also investigate relationship between soft-continuous, simply*continuous multifunction. implement...

In this paper, by presenting some notions and theorems, we obtaindifferent types of fuzzy topologies. In fact, we obtain someLowen-type  and Chang-type fuzzy topologies on general fuzzyautomata. To this end, first we define a Kuratowski fuzzy interioroperator which induces a  Lowen-type  fuzzy topology on the  set ofstates of a max- min general   fuzzy automaton. Also by  provingsome theorems, ...

D. Molodtsov (1999) introduced the concept of a soft set as a new approach for modeling uncertainties. The aim of this work is to define special kinds of soft sets, namely soft, L-fuzzifying soft, L-soft, and L-fuzzy soft neighborhood sets and to use them in order to give an alternative characterization of categories related to topology: crisp topological, L-topological, L-fuzzifying topologica...

Elimination of redundancies in the memory representation is necessary for fast and efficient analysis of large sets of fuzzy data. In this work, we use MTBDDs as the underlying data-structure to represent fuzzy sets and binary fuzzy relations. This leads to elimination of redundancies in the representation, less computations, and faster analyses. We also extended a BDD package (BuDDy) to suppor...