• Title/Summary/Keyword: Mathematical function

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CONSTANTS FOR HARMONIC MAPPINGS

  • Jun, Sook Heui
    • Journal of the Chungcheong Mathematical Society
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    • v.17 no.2
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    • pp.163-167
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    • 2004
  • In this paper, we obtain some coefficient estimates of harmonic, orientation-preserving, univalent mappings defined on ${\Delta}$ = {z : |z| > 1}.

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RECURSIONS FOR TRACES OF SINGULAR MODULI

  • Kim, Chang Heon
    • Journal of the Chungcheong Mathematical Society
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    • v.21 no.2
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    • pp.183-188
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    • 2008
  • We will derive recursion formulas satisfied by the traces of singular moduli for the higher level modular function.

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ON ESTIMATES OF POISSON KERNELS FOR SYMMETRIC LÉVY PROCESSES

  • Kang, Jaehoon;Kim, Panki
    • Journal of the Korean Mathematical Society
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    • v.50 no.5
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    • pp.1009-1031
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    • 2013
  • In this paper, using elementary calculus only, we give a simple proof that Green function estimates imply the sharp two-sided pointwise estimates for Poisson kernels for subordinate Brownian motions. In particular, by combining the recent result of Kim and Mimica [5], our result provides the sharp two-sided estimates for Poisson kernels for a large class of subordinate Brownian motions including geometric stable processes.

VALUE DISTRIBUTION OF SOME q-DIFFERENCE POLYNOMIALS

  • Xu, Na;Zhong, Chun-Ping
    • Bulletin of the Korean Mathematical Society
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    • v.53 no.1
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    • pp.29-38
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    • 2016
  • For a transcendental entire function f(z) with zero order, the purpose of this article is to study the value distributions of q-difference polynomial $f(qz)-a(f(z))^n$ and $f(q_1z)f(q_2z){\cdots}f(q_mz)-a(f(z))^n$. The property of entire solution of a certain q-difference equation is also considered.

DEGREE OF APPROXIMATION TO A SMOOTH FUNCTION BY GENERALIZED TRANSLATION NETWORKS

  • HAHM, NAHMWOO;YANG, MEEHYEA;HONG, BUM IL
    • Honam Mathematical Journal
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    • v.27 no.2
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    • pp.225-232
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    • 2005
  • We obtain the approximation order to a smooth function on a compact subset of $\mathbb{R}$ by generalized translation networks. In our study, the activation function is infinitely many times continuously differentiable function but it does not have special properties around ${\infty}$ and $-{\infty}$ like a sigmoidal activation function. Using the Jackson's Theorem, we get the approximation order. Especially, we obtain the approximation order by a neural network with a fixed threshold.

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