Shahid Bahonar University of KermanJournal of Mahani Mathematical Research2251-79522220131101PERRON-FROBENIUS THEORY ON THE NUMERICAL RANGE FOR SOME CLASSES OF REAL MATRICES11585610.22103/jmmrc.2014.856ENMostafaZangiabadiDEPARTMENT OF MATHEMATICS, HORMOZGAN UNIVERSITY, P. O. BOX 3995,
BANDAR ABBAS, IRAN0000-0003-4472-3609Hamid RezaAfshinDepartment of Mathematics, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran.Journal Article20131203We give further results for Perron-Frobenius theory on the numerical<br />range of real matrices and some other results generalized from nonnegative matrices<br />to real matrices. We indicate two techniques for establishing the main theorem of<br />Perron and Frobenius on the numerical range. In the rst method, we use a<br />corresponding version of Wielandt's lemma. The second technique involves graph<br />theory.https://jmmrc.uk.ac.ir/article_856_4163809109f91cfe3ad4ec8517d70609.pdfShahid Bahonar University of KermanJournal of Mahani Mathematical Research2251-79522220131101RELATIVE INFORMATION FUNCTIONAL OF RELATIVE
DYNAMICAL SYSTEMS172886510.22103/jmmrc.2014.865ENUOSEFMOHAMMADIDEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE
UNIVERSITY OF JIROFT , JIROFT, IRAN, 78671-61167.0000-0002-4059-4144Journal Article20131203 In this paper by use of mathematical modeling of an observer [14,<br />15] the notion of relative information functional for relative dynamical systems<br />on compact metric spaces is presented. We extract the information function of<br />an ergodic dynamical system (X,T) from the relative information of T from<br />the view point of observer χX, where X denotes the base space of the system.<br />We also generalize the invariance of the information function of a dynamical<br />system , under topological isomorphism, to the relative information functional.https://jmmrc.uk.ac.ir/article_865_df2e81795f1e4313db1f89f5b63850ee.pdfShahid Bahonar University of KermanJournal of Mahani Mathematical Research2251-79522220131101PROCESS CONTROL USING ASSUMED FUZZY TEST AND FUZZY ACCEPTANCE
REGION293789010.22103/jmmrc.2015.890ENM.KHADEMIDEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE,
SHAHID BAHONAR UNIVERSITY OF KERMAN, IRANV.AMIRZADEHDEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE,
SHAHID BAHONAR UNIVERSITY OF KERMAN, IRANJournal Article20141122There are many situations for statistical process in which we have both random and vague<br />information. When uncertainty is due to fuzziness of information, fuzzy statistical control charts play an<br />important role in the monitoring process, because they simultaneously deal with both kinds of uncertainty.<br />Dealing with fuzzy characteristics using classical methods may cause the loss of information and in<br />uence<br />in process deciding making. In this paper, we proposed a decision-making process based on fuzzy rejection<br />regions and fuzzy statistical tests for crisp observation. With both methods, we dene the degree of depen-<br />dence to acceptance region for decision in the fuzzy regions and process fuzzy. A numeric example illustrates<br />the performance of the method and interprets the results.https://jmmrc.uk.ac.ir/article_890_4b869cc018665b203c6593d5a6f787e4.pdfShahid Bahonar University of KermanJournal of Mahani Mathematical Research2251-79522220131101Hyers-Ulam-Rassias Stability of Functional Equations on Fuzzy Normed Liner Spaces3960310410.22103/jmmrc.2021.3104ENMortezaSaheliVali-e-Asr University of Rafsanjan0000-0002-8368-1598Journal Article20141118In this paper, we use the definition of fuzzy normed spaces given by Bag and Samanta and the behaviors of solutions of the additive functional equation are described. The Hyers-Ulam stability problem of this equation is discussed and theorems concerning the Hyers-Ulam-Rassias stability of the equation are proved on fuzzy normed linear space.https://jmmrc.uk.ac.ir/article_3104_36483b7b147002085a360ea48f36216d.pdfShahid Bahonar University of KermanJournal of Mahani Mathematical Research2251-79522220160320The mean residual lifetime of parallel systems with two exchangeable components under the Generalized Farlie-Gumbel-Morgenstern model6172396710.22103/jmmrc.2016.1305ENSeyed ShahrokhHashemi-BosraDepartment of Basic Science, Birjand University of Technology, Birjand, IranEbrahimSalehiDepartment of Basic Science, Birjand University of Technology, Birjand, Iran0000-0002-3874-0106Journal Article20151002The parallel systems are special important types of coherent structures and have many applications in various areas. In this paper we consider a two-exchangeable-component parallel system for the Generalized Farlie-Gumbel-Morgenstern (Generalized FGM) distribution. We study the reliability properties of the residual lifetime of the system under the condition that both components of the system are operating at time $t$, and obtain an explicit expression for the mean residual lifetime (MRL) for such system. The asymptotic behavior of the proposed MRL function of the system is also investigated when the exchangeable lifetimes of components have a Generalized FGM bivariate exponential. Finally, we present some results for the correlation coefficient Kendall's Tau of Generalized FGM bivariate copula.https://jmmrc.uk.ac.ir/article_3967_cd1e13af7b969c799262138e1fc2b956.pdfShahid Bahonar University of KermanJournal of Mahani Mathematical Research2251-79522220131101Linear Hypothesis Testing using D_LR Metric7387396810.22103/jmmrc.2013.1398ENAlirezaArabpourDepartment of Statistics, Shahid Bahonar University of Kerman, Kerman, Iran0000-0001-5287-2263MahdiehMozafariDepartment of Statistics, Higher Education Complex of Bam, Kerman, IranJournal Article20160410Several practical problems of hypotheses testing can be under a general linear model analysis of variance which would be examined. In analysis of variance, when the response random variable Y , has linear relationship with several random variables x, another important model as analysis of covariance can be used.<br />In this paper, assuming that Y is fuzzy and using D_LR metric, a method for testing the linear hypothesis has been proposed based on fuzzy techniques. In fact, in this method a set of confidence intervals has been used for creating fuzzy test statistic and fuzzy critical values. In addition, the proposed method has been mentioned for the reforming of the hypothesis testing when there is an uncertaity in accepting or rejecting hypotheses. Finally, by presenting two examples this method is illustrated.https://jmmrc.uk.ac.ir/article_3968_7369521e11a8d017ce729aeb1e32aa38.pdf