• Title/Summary/Keyword: logarithmic order

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EXISTENCE OF GENERALISED LOGARITHMIC PROXIMATE ORDER AND GENERALISED LOGARITHMIC PROXIMATE TYPE OF AN ENTIRE FUNCTION

  • Ghosh, Chinmay;Mondal, Sutapa;Khan, Subhadip
    • Korean Journal of Mathematics
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    • v.29 no.1
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    • pp.179-191
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    • 2021
  • In this paper we introduce generalised logarithmic proximate order, generalised logarithmic proximate type of an entire function and prove the corresponding existence theorems. Also we investigate some theorems on the application of generalised logarithmic proximate order.

RELATIVE LOGARITHMIC ORDER OF AN ENTIRE FUNCTION

  • Ghosh, Chinmay;Bandyopadhyay, Anirban;Mondal, Soumen
    • Korean Journal of Mathematics
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    • v.29 no.1
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    • pp.105-120
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    • 2021
  • In this paper, we extend some results related to the growth rates of entire functions by introducing the relative logarithmic order ����g(f) of a nonconstant entire function f with respect to another nonconstant entire function g. Next we investigate some theorems related the behavior of ����g(f). We also define the relative logarithmic proximate order of f with respect to g and give some theorems on it.

FINITE LOGARITHMIC ORDER SOLUTIONS OF LINEAR q-DIFFERENCE EQUATIONS

  • Wen, Zhi-Tao
    • Bulletin of the Korean Mathematical Society
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    • v.51 no.1
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    • pp.83-98
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    • 2014
  • During the last decade, several papers have focused on linear q-difference equations of the form ${\sum}^n_{j=0}a_j(z)f(q^jz)=a_{n+1}(z)$ with entire or meromorphic coefficients. A tool for studying these equations is a q-difference analogue of the lemma on the logarithmic derivative, valid for meromorphic functions of finite logarithmic order ${\rho}_{log}$. It is shown, under certain assumptions, that ${\rho}_{log}(f)$ = max${{\rho}_{log}(a_j)}$ + 1. Moreover, it is illustrated that a q-Casorati determinant plays a similar role in the theory of linear q-difference equations as a Wronskian determinant in the theory of linear differential equations. As a consequence of the main results, it follows that the q-gamma function and the q-exponential functions all have logarithmic order two.

GROWTH OF SOLUTIONS OF LINEAR DIFFERENTIAL-DIFFERENCE EQUATIONS WITH COEFFICIENTS HAVING THE SAME LOGARITHMIC ORDER

  • Biswas, Nityagopal
    • Korean Journal of Mathematics
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    • v.29 no.3
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    • pp.473-481
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    • 2021
  • In this paper, we investigate the relations between the growth of meromorphic coefficients and that of meromorphic solutions of complex linear differential-difference equations with meromorphic coefficients of finite logarithmic order. Our results can be viewed as the generalization for both the cases of complex linear differential equations and complex linear difference equations.

AN EXACT LOGARITHMIC-EXPONENTIAL MULTIPLIER PENALTY FUNCTION

  • Lian, Shu-jun
    • Journal of applied mathematics & informatics
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    • v.28 no.5_6
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    • pp.1477-1487
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    • 2010
  • In this paper, we give a solving approach based on a logarithmic-exponential multiplier penalty function for the constrained minimization problem. It is proved exact in the sense that the local optimizers of a nonlinear problem are precisely the local optimizers of the logarithmic-exponential multiplier penalty problem.

A NONLINEAR CONVEX SPLITTING FOURIER SPECTRAL SCHEME FOR THE CAHN-HILLIARD EQUATION WITH A LOGARITHMIC FREE ENERGY

  • Kim, Junseok;Lee, Hyun Geun
    • Bulletin of the Korean Mathematical Society
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    • v.56 no.1
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    • pp.265-276
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    • 2019
  • For a simple implementation, a linear convex splitting scheme was coupled with the Fourier spectral method for the Cahn-Hilliard equation with a logarithmic free energy. However, an inappropriate value of the splitting parameter of the linear scheme may lead to incorrect morphologies in the phase separation process. In order to overcome this problem, we present a nonlinear convex splitting Fourier spectral scheme for the Cahn-Hilliard equation with a logarithmic free energy, which is an appropriate extension of Eyre's idea of convex-concave decomposition of the energy functional. Using the nonlinear scheme, we derive a useful formula for the relation between the gradient energy coefficient and the thickness of the interfacial layer. And we present numerical simulations showing the different evolution of the solution using the linear and nonlinear schemes. The numerical results demonstrate that the nonlinear scheme is more accurate than the linear one.

ADAPTATION OF THE MINORANT FUNCTION FOR LINEAR PROGRAMMING

  • Leulmi, S.;Leulmi, A.
    • East Asian mathematical journal
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    • v.35 no.5
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    • pp.597-612
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    • 2019
  • In this study, we propose a new logarithmic barrier approach to solve linear programming problem using the projective method of Karmarkar. We are interested in computation of the direction by Newton's method and of the step-size using minorant functions instead of line search methods in order to reduce the computation cost. Our new approach is even more beneficial than classical line search methods. We reinforce our purpose by many interesting numerical simulations proved the effectiveness of the algorithm developed in this work.

ON THE $FEKETE-SZEG\"{O}$ PROBLEM FOR STRONGLY $\alpha$-LOGARITHMIC CLOSE-TO-CONVEX FUNCTIONS

  • Cho, Nak-Eun
    • East Asian mathematical journal
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    • v.21 no.2
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    • pp.233-240
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    • 2005
  • Let $CS^{\alpha}(\beta)$ denote the class of normalized strongly $\alpha$-logarithmic close-to-convex functions of order $\beta$, defined in the open unit disk $\mathbb{U}$ by $$\|arg\{\(\frac{f(z)}{g(z)}\)^{1-\alpha}\(\frac{zf'(z)}{g(z)\)^{\alpha}\}\|\leq\frac{\pi}{2}\beta,\;(\alpha,\beta\geq0)$$ where $g{\in}S^*$ the class of normalized starlike functions. In this paper, we prove sharp $Fekete-Szeg\"{o}$ inequalities for functions $f{\in}CS^{\alpha}(\beta)$.

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THE LOGARITHMIC KUMARASWAMY FAMILY OF DISTRIBUTIONS: PROPERTIES AND APPLICATIONS

  • Ahmad, Zubair
    • Communications of the Korean Mathematical Society
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    • v.34 no.4
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    • pp.1335-1352
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    • 2019
  • In this article, a new family of lifetime distributions by adding two additional parameters is introduced. The new family is called, the logarithmic Kumaraswamy family of distributions. For the proposed family, explicit expressions for some mathematical properties are derived. Maximum likelihood estimates of the model parameters are also obtained. This method is applied to develop a new lifetime model, called the logarithmic Kumaraswamy Weibull distribution. The proposed model is very flexible and capable of modeling data with increasing, decreasing, unimodal or modified unimodal shaped hazard rates. To access the behavior of the model parameters, a simulation study has been carried out. Finally, the potentiality of the new method is proved via analyzing two real data sets.