The logical foundations of processes handling uncertainty in information use some classes of algebras as algebraic semantics. The sets of provable formulas in corresponding inference systems from the point of view of uncertain information can be described by fuzzy filters of those algebraic semantics. Bounded residuated lattice ordered monoids (R`-monoids) are a common generalization of pseudo ...

G-Frames in Hilbert spaces are a redundant set of operators which yield a representation for each vector in the space. In this paper we investigate the connection between g-frames, g-orthonormal bases and g-Riesz bases. We show that a family of bounded operators is a g-Bessel sequences if and only if the Gram matrix associated to its denes a bounded operator.

We present a method for incremental modeling and time-varying control of unknown nonlinear systems. The combines elements evolving intelligence, granular machine learning, multi-variable control. propose State-Space Fuzzy-set-Based Modeling (SS-FBeM) approach. resulting fuzzy model is structurally parametrically developed from data stream with focus on memory coverage. controller also evolves, ...

This paper presents the robust fuzzy fault tolerant control (FFTC) for nonlinear wind energy conversion systems (WECS) in the presence of bounded sensor faults and the state variable unavailable for measurement based on Takagi-Sugeno (TS) fuzzy model. Sufficient conditions are derived for robust stabilization in the sense of Lyapunov asymptotic stability and are formulated in the format of line...

A set S of vertices in a graph G=(V,E) is a dominating set ofG if every vertex of V-S is adjacent to some vertex of S.For an integer k≥1, a set S of vertices is a k-step dominating set if any vertex of $G$ is at distance k from somevertex of S. In this paper, using membership values of vertices and edges in fuzzy graphs, we introduce the concepts of strength of strongestdominating set as well a...

recently, gasimov and yenilmez proposed an approach for solving two kinds of fuzzy linear programming (flp) problems. through the approach, each flp problem is first defuzzified into an equivalent crisp problem which is non-linear and even non-convex. then, the crisp problem is solved by the use of the modified subgradient method. in this paper we will have another look at the earlier defuzzifi...