In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global converge...

In this paper Hermite—Hadamard type inequalities for m-convex and (α,m)-convex functions for fuzzy integrals are given. Some examples are also given to illustrate the results.

Abstract In this paper, the convex nonsmooth optimization problem with fuzzy objective function and both inequality equality constraints is considered. The Karush–Kuhn–Tucker necessary optimality conditions are proved for such a extremum problem. Further, exact $$l_{1}$$ l 1 </mml:...

To date, nonlinear l∞ -gain static output feedback control problems have not been solved by the conventional control methods for nonlinear discrete-time systems with persistent bounded disturbances. This study introduces static output feedback fuzzy control scheme to deal with the nonlinear l∞ -gain control problem. The structure of static output feedback fuzzy control is simpler than that of d...

In the case of real-valued inputs, averaging aggregation functions have been studied extensively with results arising in fields including probability and statistics, fuzzy decision-making, and various sciences. Although much of the behavior of aggregation functions when combining standard fuzzy membership values is well established, extensions to interval-valued fuzzy sets, hesitant fuzzy sets,...

in this paper, the notion of fuzzy semicompactness degrees isintroduced in $l$-fuzzy topological spaces by means of theimplication operation of $l$. characterizations of fuzzysemicompactness degrees in $l$-fuzzy topological spaces  areobtained, and some properties of fuzzy semicompactness degrees areresearched.

Abstract In this paper, we introduce the non-convex interval-valued functions for fuzzy-interval-valued functions, which are called "Equation missing"-convex by means of fuzzy order relation. This relation is defined level-wise through Kulisch–Miranker given on interval space. By using -->-convexity concept, present fuzzy-interval Hermite–Hadamard inequali...

following the idea of $l$-fuzzy neighborhood system as introduced byfu-gui shi, and its generalization to $(l,m)$-fuzzy neighborhood system, the relationship between  $(l,m)$-fuzzy topology and $(l,m)$-fuzzy neighborhood system will be further studied. as an application of the obtained results, we will describe the initial structures of $(l,m)$-fuzzy neighborhood subspaces and $(l,m)$-fuzzy top...

In the field of nonlinear programming (in continuous variables) convex analysis [22, 23] plays a pivotal role both in theory and in practice. An analogous theory for discrete optimization (nonlinear integer programming), called " discrete convex analysis " [18, 17], is developed for L-convex and M-convex functions by adapting the ideas in convex analysis and generalizing the results in matroid ...