فهرست مطالب
Journal of Mahani Mathematical Research
Volume:7 Issue: 2, Summer and Autumn 2018
- تاریخ انتشار: 1397/07/09
- تعداد عناوین: 4
-
Pages 57-77Taking into account the notion of BL-general fuzzy automaton, in the present study we define the notation of BL-intuitionistic general L-fuzzy automaton and I-bisimulation for BL-intuitionistic general L-fuzzy automaton.Then for a given BL-intuitionistic general L-fuzzy automaton, we obtain the greatest I-bisimulation. According to this notion, we give the structure of quotient BL-intuitionistic general L-fuzzy automaton. Fortunately, this quotient is the minimal BL-intuitionistic general L-fuzzy automaton. In addition, in this study, we show that if there is an I-bisimulation between two BL-intuitionistic general L-fuzzy automata, then they have the same behavior. Furthermore, we give an algorithm which determines the I-bisimulation between any two BL-intuitionistic general L-fuzzy automata. To clarify the notions and the results obtained in this paper, we have submitted some examples as well.Keywords: BL-general fuzzy automata, BL-intuitionistic general L-fuzzy automata, Bisimulation, Quotient automata, Minimal BL-general fuzzy automata
-
Pages 79-94ABSTRACT. Let R be a commutative noetherian ring, I and J are two ideals of R. Inthis paper we introduce the concept of (I;J)- minimax R- module, and it is shown thatif M is an (I;J)- minimax R- module and t a non-negative integer such that HiI;J(M) is(I;J)- minimax for all iKeywords: Local cohomology, cofinite module, minimax module, associated primes. 2000 Mathematics Subject Classification
-
Pages 95-104A matrix R is said to be g-row substochastic if Re ≤ e. For X, Y ∈ Mn,m, it is said that X is sglt-majorized by Y , X ≺sglt Y , if there exists an n-by-n lower triangular g-row substochastic matrix R such that X = RY . This paper characterizes all (strong) linear preservers and strong linear preservers of ≺sglt on Rn and Mn,m, respectively.Keywords: G-row substochastic matrix, Sglt-majorization, (Strong) linear preserver
-
Pages 105-125In this article, an efficient numerical technique for solving the two-dimensional time-dependent Schrodinger equation is presented. At first, we employ the meshlesslocal Petrov-Galerkin (MLPG) method based on a local weak formulation to construct a system of discretized equations and then the solution of time-dependentSchrodingerequation will be approximated. We use the Moving Kriging (MK) interpolation insteadof Moving least Square (MLS) approximation to construct the MLPG shape functionsand hence the Heaviside step function is chosen to be the test function. In this method,no mesh is needed neither for integration of the local weak form nor construction of theshape functions. So, the MLPG is truly a meshless method. Several numerical examplesare presented and the results are compared to their analytical and RBFsolutions to illustrate the accuracy and capability of this algorithm.Keywords: Meshless local Petrov-Galerkin (MLPG) method, two-dimensional time-dependent Schrodinger equation, Moving Kriging interpolation