In this research paper, we use a normalized graph cut measure as a thresholding principle to separate an object from the background based on the standard S membership function. The implementation of the proposed algorithm known as fuzzy normalized graph cut method. This proposed algorithm compared with the fuzzy entropy method [25], Kittler [11], Rosin [21], Sauvola [23] and Wolf [33] method. M...

This paper is concerned with the study of fuzzy dynamical systems. Let (XM ) be a fuzzy metric space in the sense of George and Veeramani. A fuzzy discrete dynamical system is given by any fuzzy continuous self-map dened on X. We introduce the various fuzzy shad- owing and fuzzy topological transitivity on a fuzzy discrete dynamical systems. Some relations between this notions have been proved.

Generi programming allows you to write a fun tion on e, and use it many times at di erent types. A lot of good foundational work on generi programming has been done. The goal of this paper is to propose a pra ti al way of supporting generi programming within the Haskell language, without radi ally hanging the language or its type system. The key idea is to present generi programming as a ri her...

We prove a related fixed point Theorem for four mappings which are not continuous in four fuzzy metric spaces, one of them is a sequentially compact fuzzy metric space. Our Theorem in the metric version generalizes Theorem 4 of [1]. Finally, We give a fuzzy version of Theorem 3 of [1].

In this paper, we shall introduce the fuzzyw-distance, then prove a common fixed point theorem with respectto fuzzy w-distance for two mappings under the condition ofweakly compatible in complete fuzzy metric spaces.

General topology can be regarded as a special case of fuzzy topology where all membership functions in question take values 0 and 1 only. The usual fuzzy metric spaces, fuzzy Hausdorff topological vector spaces, and Menger probabilistic metric spaces are all the special cases of F-type fuzzy topological spaces. Therefore, one would expect weaker results in the case of fuzzy topology. Recently s...

In comparison with hard clustering methods, in which a pattern belongs to a single cluster, fuzzy clustering algorithms allow patterns to belong to all clusters with differing degrees of membership. This is important in domains such as sentence clustering, since a sentence is likely to be related to more than one theme or topic present within a document or set of documents. However, because mos...

In comparison with hard clustering methods, in which a pattern belongs to a unique cluster, clustering algorithms with fuzziness allow patterns with differing degrees of membership to belong to all clusters. This is important in domains such as sentence clustering, as a sentence may belong to more than a topic present within a document or set of documents. Since most sentence similarity measure...

In this paper,  we provide two different kinds of fixed pointtheorems in  fuzzy metric spaces. The first kind is for the fuzzy$varepsilon$-contractive type mappings and  the second kind is forthe fuzzy order $psi$-contractive type mappings. They improve thecorresponding  conclusions in the literature.