• Title/Summary/Keyword: classical means

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ON THE PURE IMAGINARY QUATERNIONIC LEAST SQUARES SOLUTIONS OF MATRIX EQUATION

  • WANG, MINGHUI;ZHANG, JUNTAO
    • Journal of applied mathematics & informatics
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    • v.34 no.1_2
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    • pp.95-106
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    • 2016
  • In this paper, according to the classical LSQR algorithm forsolving least squares (LS) problem, an iterative method is proposed for finding the minimum-norm pure imaginary solution of the quaternionic least squares (QLS) problem. By means of real representation of quaternion matrix, the QLS's correspongding vector algorithm is rewrited back to the matrix-form algorthm without Kronecker product and long vectors. Finally, numerical examples are reported that show the favorable numerical properties of the method.

A Bayesian Test Criterion for the Behrens-Firsher Problem

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.6 no.1
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    • pp.193-205
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    • 1999
  • An approximate Bayes criterion for Behrens-Fisher problem (testing equality of means of two normal populations with unequal variances) is proposed and examined. Development of the criterion involves derivation of approximate Bayes factor using the imaginary training sample approachintroduced by Spiegelhalter and Smith (1982). The proposed criterion is designed to develop a Bayesian test criterion having a closed form, so that it provides an alternative test to those based upon asymptotic sampling theory (such as Welch's t test). For the suggested Bayes criterion, numerical study gives comparisons with a couple of asymptotic classical test criteria.

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A boundary element approach for quasibrittle fracture propagation analysis

  • Tin-Loi, F.
    • Structural Engineering and Mechanics
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    • v.8 no.5
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    • pp.439-452
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    • 1999
  • A simple numerical scheme suitable for tracing the fracture propagation path for structures idealized by means of Hillerborg's classical cohesive crack model is presented. A direct collocation, multidomain boundary element method is adopted for the required space discretization. The algorithm proposed is necessarily iterative in nature since the crack itinerary is a priori unknown. The fracture process is assumed to be governed by a path-dependent generally nonlinear softening law. The potentialities of the method are illustrated through two examples.

A Study on Key Generation using the Real Random Number Generator (실 난수 발생기를 이용한 키 생성에 관한 연구)

  • 차재현;박중길;전문석
    • The Journal of Society for e-Business Studies
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    • v.6 no.2
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    • pp.167-178
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    • 2001
  • Key is generally formed using the Random Number. How to make the Random Number is to cast coin or dice as classical method, to form the Real Random Number with Hardware and to make the Pseudo Random Number by means of utilizing mathematical algorithm. This thesis presented NRNG(New Random Number Generator) which put self-development Hardware to use as Key Generation Method and inspected to compare the Real Random Number with the Pseudo Random Number and special properties which PRNG(Pseudo-Random Number Generator) creates.

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Development of New Strategies for Enzyme Replacement Therapy for Lysosomal Storage Disorders

  • Ko, Ah-Ra
    • Journal of mucopolysaccharidosis and rare diseases
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    • v.2 no.1
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    • pp.17-18
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    • 2016
  • Enzyme replacement therapy (ERT) is a well-established means of treating lysosomal storage disease (LSD). However, classical IV infusion based ERT method produces less than ideal results, especially, CNS defects and quality of life in patients. To improve these main problems of parental IV formulation for LSDs, we investigate modified ERT method and evaluated the efficacy in animal model.

Non-associative fuzzy-relevance logics: strong t-associative monoidal uninorm logics

  • Yang, Eun-Suk
    • Korean Journal of Logic
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    • v.12 no.1
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    • pp.89-110
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    • 2009
  • This paper investigates generalizations of weakening-free uninorm logics not assuming associativity of intensional conjunction (so called fusion) &, as non-associative fuzzy-relevance logics. First, the strong t-associative monoidal uninorm logic StAMUL and its schematic extensions are introduced as non-associative propositional fuzzy-relevance logics. (Non-associativity here means that, differently from classical logic, & is no longer associative.) Then the algebraic structures corresponding to the systems are defined, and algebraic completeness results for them are provided. Next, predicate calculi corresponding to the propositional systems introduced here are considered.

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Modeling of Structure of the Specialized Processor on the Basis Ryabenko's Splines for Signal Processing

  • Zaynidinov, Hakimjon;Nishonboev, Golibjon
    • Journal of information and communication convergence engineering
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    • v.9 no.4
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    • pp.424-427
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    • 2011
  • The paper is devoted to problem of spline approximation. A new method of nodes location for curves and surfaces computer construction by means of B-splines, of Reyabenko's splines and results of simulink-modeling is presented. The advantages of this paper is that we comprise the basic spline with classical polynomials both on accuracy, as well as degree of paralleling calculations are also show's.

A Bayes-P* Selection Procedure for Normal Means with Common Unknown Variance+ (분산이 미지인 정규모집단의 평균에 대한 베이즈-P* 선택방법에 관한 연구+)

  • 김우철;전종우;한경수
    • The Korean Journal of Applied Statistics
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    • v.3 no.2
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    • pp.79-89
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    • 1990
  • For selecting a subset of k normal populations containing the one with the largest mean, a Bayes-$P^*$ selection procedure is considered when the common variance is unknown. Performance of the Bayes-$P^*$ selection procedure is compared with a well known classical procedure through a simulation study. Some frequentist's characteristics of Bayes-$P^*$ procedure are also studied.

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A Support Vector Method for the Deconvolution Problem

  • Lee, Sung-Ho
    • Communications for Statistical Applications and Methods
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    • v.17 no.3
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    • pp.451-457
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    • 2010
  • This paper considers the problem of nonparametric deconvolution density estimation when sample observa-tions are contaminated by double exponentially distributed errors. Three different deconvolution density estima-tors are introduced: a weighted kernel density estimator, a kernel density estimator based on the support vector regression method in a RKHS, and a classical kernel density estimator. The performance of these deconvolution density estimators is compared by means of a simulation study.

A NEW EXTENSION OF BESSEL FUNCTION

  • Chudasama, Meera H.
    • Communications of the Korean Mathematical Society
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    • v.36 no.2
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    • pp.277-298
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    • 2021
  • In this paper, we propose an extension of the classical Bessel function by means of our ℓ-hypergeometric function [2]. As the main results, the infinite order differential equation, the generating function relation, and contour integral representations including Schläfli's integral analogue are derived. With the aid of these, other results including some inequalities are also obtained. At the end, the graphs of these functions are plotted using the Maple software.