ORIGINAL_ARTICLE
PERRON-FROBENIUS THEORY ON THE NUMERICAL RANGE FOR SOME CLASSES OF REAL MATRICES
We give further results for Perron-Frobenius theory on the numericalrange of real matrices and some other results generalized from nonnegative matricesto real matrices. We indicate two techniques for establishing the main theorem ofPerron and Frobenius on the numerical range. In the rst method, we use acorresponding version of Wielandt's lemma. The second technique involves graphtheory.
http://jmmrc.uk.ac.ir/article_856_4163809109f91cfe3ad4ec8517d70609.pdf
2014-11-23T11:23:20
2018-08-21T11:23:20
1
15
10.22103/jmmrc.2014.856
sign-real numerical radius
sign-real spectral radius
Perron-Frobenius
theory
signature matrices
numerical range
MOSTAFA
ZANGIABADI
zangiabadi@hormozgan.ac.ir
true
1
DEPARTMENT OF MATHEMATICS, HORMOZGAN UNIVERSITY, P. O. BOX 3995,
BANDAR ABBAS, IRAN
DEPARTMENT OF MATHEMATICS, HORMOZGAN UNIVERSITY, P. O. BOX 3995,
BANDAR ABBAS, IRAN
DEPARTMENT OF MATHEMATICS, HORMOZGAN UNIVERSITY, P. O. BOX 3995,
BANDAR ABBAS, IRAN
AUTHOR
HAMID REZA
AFSHIN
afshin@vru.ac.ir
true
2
DEPARTMENT OF MATHEMATICS, VALI-E-ASR UNIVERSITY OF RAFSANJAN,
P. O. BOX 518, RAFSANJAN, IRAN
DEPARTMENT OF MATHEMATICS, VALI-E-ASR UNIVERSITY OF RAFSANJAN,
P. O. BOX 518, RAFSANJAN, IRAN
DEPARTMENT OF MATHEMATICS, VALI-E-ASR UNIVERSITY OF RAFSANJAN,
P. O. BOX 518, RAFSANJAN, IRAN
LEAD_AUTHOR
ORIGINAL_ARTICLE
RELATIVE INFORMATION FUNCTIONAL OF RELATIVE
DYNAMICAL SYSTEMS
In this paper by use of mathematical modeling of an observer [14,15] the notion of relative information functional for relative dynamical systemson compact metric spaces is presented. We extract the information function ofan ergodic dynamical system (X,T) from the relative information of T fromthe view point of observer χX, where X denotes the base space of the system.We also generalize the invariance of the information function of a dynamicalsystem , under topological isomorphism, to the relative information functional.
http://jmmrc.uk.ac.ir/article_865_df2e81795f1e4313db1f89f5b63850ee.pdf
2014-12-21T11:23:20
2018-08-21T11:23:20
17
28
10.22103/jmmrc.2014.865
Information function
relative dynamical system
relative generator
relative measure
relative information functional
UOSEF
MOHAMMADI
u.mohamadi@ujiroft.ac.ir
true
1
DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE
UNIVERSITY OF JIROFT , JIROFT, IRAN, 78671-61167.
DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE
UNIVERSITY OF JIROFT , JIROFT, IRAN, 78671-61167.
DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE
UNIVERSITY OF JIROFT , JIROFT, IRAN, 78671-61167.
LEAD_AUTHOR
ORIGINAL_ARTICLE
PROCESS CONTROL USING ASSUMED FUZZY TEST AND FUZZY ACCEPTANCE
REGION
There are many situations for statistical process in which we have both random and vagueinformation. When uncertainty is due to fuzziness of information, fuzzy statistical control charts play animportant role in the monitoring process, because they simultaneously deal with both kinds of uncertainty.Dealing with fuzzy characteristics using classical methods may cause the loss of information and inuencein process deciding making. In this paper, we proposed a decision-making process based on fuzzy rejectionregions and fuzzy statistical tests for crisp observation. With both methods, we dene the degree of depen-dence to acceptance region for decision in the fuzzy regions and process fuzzy. A numeric example illustratesthe performance of the method and interprets the results.
http://jmmrc.uk.ac.ir/article_890_4b869cc018665b203c6593d5a6f787e4.pdf
2015-03-01T11:23:20
2018-08-21T11:23:20
29
37
10.22103/jmmrc.2015.890
fuzzy hypotheses testing
fuzzy rejection region
hybrid numbers
M.
KHADEMI
mahdiyeh khademi@yahoo.com
true
1
DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE,
SHAHID BAHONAR UNIVERSITY OF KERMAN, IRAN
DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE,
SHAHID BAHONAR UNIVERSITY OF KERMAN, IRAN
DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE,
SHAHID BAHONAR UNIVERSITY OF KERMAN, IRAN
AUTHOR
V.
AMIRZADEH
v_amirzadeh@uk.ac.ir
true
2
DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE,
SHAHID BAHONAR UNIVERSITY OF KERMAN, IRAN
DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE,
SHAHID BAHONAR UNIVERSITY OF KERMAN, IRAN
DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE,
SHAHID BAHONAR UNIVERSITY OF KERMAN, IRAN
LEAD_AUTHOR
ORIGINAL_ARTICLE
HYERS-ULAM-RASSIAS STABILITY OF FUNCTIONAL EQUATIONS ON FUZZY NORMED LINER SPACES
In this paper, we use the denition of fuzzy normed spaces givenby Bag and Samanta and the behaviors of solutions of the additive functionalequation are described. The Hyers-Ulam stability problem of this equationis discussed and theorems concerning the Hyers-Ulam-Rassias stability of theequation are proved on fuzzy normed linear space.
http://jmmrc.uk.ac.ir/article_1128_308a48da0e9c5a0cd05bc30a04b557b1.pdf
2016-01-01T11:23:20
2018-08-21T11:23:20
39
60
10.22103/jmmrc.2016.1128
Fuzzy norm
Fuzzy normed linear space
Functional equation
M.
SAHELI
saheli@vru.ac.ir
true
1
DEPARTMENT OF OF MATHEMATICS
VALI-E-ASR UNIVERSITY OF RAFSANJAN, RAFSANJAN, IRAN
DEPARTMENT OF OF MATHEMATICS
VALI-E-ASR UNIVERSITY OF RAFSANJAN, RAFSANJAN, IRAN
DEPARTMENT OF OF MATHEMATICS
VALI-E-ASR UNIVERSITY OF RAFSANJAN, RAFSANJAN, IRAN
LEAD_AUTHOR
ORIGINAL_ARTICLE
THE MEAN RESIDUAL LIFETIME OF PARALLEL SYSTEMS WITH TWO EXCHANGEABLE COMPONENTS UNDER THE GENERALIZED FARLIE-GUMBEL-MORGENSTERN MODEL
The 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 Kendall’s Tau correlation coefficient of Generalized FGM bivariate copula.
http://jmmrc.uk.ac.ir/article_1305_700a00b64730d6a670fc31ed002ab541.pdf
2016-03-12T11:23:20
2018-08-21T11:23:20
61
72
10.22103/jmmrc.2016.1305
mean residual lifetime
copula
exponential distribution
Reliability
S. S.
HASHEMI-BOSRA
true
1
DEPARTMENT OF BASIC SCIENCES, BIRJAND UNIVERSITY OF
TECHNOLOGY, BIRJAND 97198, IRAN
DEPARTMENT OF BASIC SCIENCES, BIRJAND UNIVERSITY OF
TECHNOLOGY, BIRJAND 97198, IRAN
DEPARTMENT OF BASIC SCIENCES, BIRJAND UNIVERSITY OF
TECHNOLOGY, BIRJAND 97198, IRAN
AUTHOR
E.
SALEHI
salehi@birjandut.ac.ir
true
2
DEPARTMENT OF BASIC SCIENCES, BIRJAND UNIVERSITY OF
TECHNOLOGY, BIRJAND 97198, IRAN
DEPARTMENT OF BASIC SCIENCES, BIRJAND UNIVERSITY OF
TECHNOLOGY, BIRJAND 97198, IRAN
DEPARTMENT OF BASIC SCIENCES, BIRJAND UNIVERSITY OF
TECHNOLOGY, BIRJAND 97198, IRAN
LEAD_AUTHOR
ORIGINAL_ARTICLE
LINEAR HYPOTHESIS TESTING USING DLR METRIC
Several 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. In this paper, assuming that Y is fuzzy and using DLR metric, a method for testing the linear hypothesis has been proposed based on fuzzy techniques. In fact, in this method a set of condence 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. The result are illustrated by the means of some case studies.
http://jmmrc.uk.ac.ir/article_1398_8dde855722d56c643b869ec6fd428d05.pdf
2013-12-30T11:23:20
2018-08-21T11:23:20
73
87
10.22103/jmmrc.2013.1398
Analysis of covariance
Buckley's method
Confidence interval
DLR
metric
Fuzzy test statistic
ALIREZA
ARABPOUR
arabpour@uk.ac.ir
true
1
DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND
COMPUTER, SHAHID BAHONAR UNIVERSITY OF KERMAN, KERMAN,
IRAN
DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND
COMPUTER, SHAHID BAHONAR UNIVERSITY OF KERMAN, KERMAN,
IRAN
DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND
COMPUTER, SHAHID BAHONAR UNIVERSITY OF KERMAN, KERMAN,
IRAN
LEAD_AUTHOR
MAHDIEH
MOZAFARI
mozafari@bam.ac.ir
true
2
DEPARTMENT OF STATISTICS, HIGHER EDUCATION COMPLEX OF
BAM, KERMAN, IRAN
DEPARTMENT OF STATISTICS, HIGHER EDUCATION COMPLEX OF
BAM, KERMAN, IRAN
DEPARTMENT OF STATISTICS, HIGHER EDUCATION COMPLEX OF
BAM, KERMAN, IRAN
AUTHOR