• Title/Summary/Keyword: Estimates

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CHARACTERIZATION THEOREMS OF RILEY TYPE FOR BICOMPLEX HOLOMORPHIC FUNCTIONS

  • Matsui, Yutaka;Sato, Yuhei
    • Communications of the Korean Mathematical Society
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    • v.35 no.3
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    • pp.825-841
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    • 2020
  • We characterize bicomplex holomorphic functions from several estimates. Originally, Riley [5] studied such problems in local case. In our study, we treat global estimates on various unbounded domains. In many cases, we can determine the explicit form of a function.

SOME BILINEAR ESTIMATES

  • Chen, Jiecheng;Fan, Dashan
    • Journal of the Korean Mathematical Society
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    • v.46 no.3
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    • pp.609-620
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    • 2009
  • We establish some estimates on the hyper bilinear Hilbert transform on both Euclidean space and torus. We also use a transference method to obtain a Kenig-Stein's estimate on bilinear fractional integrals on the n-torus.

An adaption algorithm for parallel model reference bilinear systems

  • Yeo, Yeong-Koo;Song, Hyung-Keun
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10a
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    • pp.721-723
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    • 1987
  • An Adaptation algorithm is presented and a convergence criterion is derived for parallel model reference adaptive bilinear systems. The output error converges asymptotically to zero, and the parameter estimates are bounded for stable reference models. The convergence criterion depends only upon the input sequence and a priori estimates of the maximum parameter values.

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A PRIORI ERROR ESTIMATES FOR THE FINITE ELEMENT APPROXIMATION OF AN OBSTACLE PROBLEM

  • Ryoo, Cheon-Seoung
    • Journal of applied mathematics & informatics
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    • v.7 no.1
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    • pp.175-181
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    • 2000
  • The purpose of this to measure, with explicit constants as small as possible, a priori error bounds for approximation by picewise polynomials. These constants play an important role in the numerical verification method of solutions for obstacle problems by using finite element methods .

Diagnostic for Smoothing Parameter Estimate in Nonparametric Regression Model

  • In-Suk Lee;Won-Tae Jung
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.266-276
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    • 1995
  • We have considered the study of local influence for smoothing parameter estimates in nonparametric regression model. Practically, generalized cross validation(GCV) does not work well in the presence of data perturbation. Thus we have proposed local influence measures for GCV estimates and examined effects of diagnostic by above measures.

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