• 제목/요약/키워드: linear convergence

검색결과 1,328건 처리시간 0.024초

AN ACCELERATING SCHEME OF CONVERGENCE TO SOLVE FUZZY NON-LINEAR EQUATIONS

  • Jun, Younbae
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제24권1호
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    • pp.45-51
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    • 2017
  • In this paper, we propose an accelerating scheme of convergence of numerical solutions of fuzzy non-linear equations. Numerical experiments show that the new method has significant acceleration of convergence of solutions of fuzzy non-linear equation. Three-dimensional graphical representation of fuzzy solutions is also provided as a reference of visual convergence of the solution sequence.

Stable Tracking Control to a Non-linear Process Via Neural Network Model

  • Zhai, Yujia
    • 한국융합학회논문지
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    • 제5권4호
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    • pp.163-169
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    • 2014
  • A stable neural network control scheme for unknown non-linear systems is developed in this paper. While the control variable is optimised to minimize the performance index, convergence of the index is guaranteed asymptotically stable by a Lyapnov control law. The optimization is achieved using a gradient descent searching algorithm and is consequently slow. A fast convergence algorithm using an adaptive learning rate is employed to speed up the convergence. Application of the stable control to a single input single output (SISO) non-linear system is simulated. The satisfactory control performance is obtained.

COMPLETE f-MOMENT CONVERGENCE FOR EXTENDED NEGATIVELY DEPENDENT RANDOM VARIABLES UNDER SUB-LINEAR EXPECTATIONS

  • Lu, Chao;Wang, Rui;Wang, Xuejun;Wu, Yi
    • 대한수학회지
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    • 제57권6호
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    • pp.1485-1508
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    • 2020
  • In this paper, we investigate the complete f-moment convergence for extended negatively dependent (END, for short) random variables under sub-linear expectations. We extend some results on complete f-moment convergence from the classical probability space to the sub-linear expectation space. As applications, we present some corollaries on complete moment convergence for END random variables under sub-linear expectations.

On the fuzzy convergence of sequences in a fuzzy normed linear space

  • Rhie, Gil-Seob;Hwang, In-Ah
    • 한국지능시스템학회논문지
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    • 제18권2호
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    • pp.268-271
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    • 2008
  • In this paper, we introduce the notions of a fuzzy convergence of sequences, fuzzy Cauchy sequence and the related fuzzy completeness on a fuzzy normed linear space. And we investigate some properties relative to fuzzy normed linear spaces. In particular, we prove an equivalent conditions that a fuzzy norm defined on a ordinary normed linear space is fuzzy complete.

Rate of Convergence of Empirical Distributions and Quantiles in Linear Processes with Applications to Trimmed Mean

  • Lee, Sangyeol
    • Journal of the Korean Statistical Society
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    • 제28권4호
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    • pp.435-441
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    • 1999
  • A 'convergence in probability' rate of the empirical distributions and quantiles of linear processes is obtained. As an application of the limit theorems, a trimmed mean for the location of the linear process is considered. It is shown that the trimmed mean is asymptotically normal. A consistent estimator for the asymptotic variance of the trimmed mean is provided.

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A Weak Convergence of the Linear Random Field Generated by Associated Randomvariables ℤ2

  • Kim, Tae-Sung;Ko, Mi-Hwa;Kim, Hyun-Chull
    • Communications for Statistical Applications and Methods
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    • 제15권6호
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    • pp.959-967
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    • 2008
  • In this paper we show the weak convergence of the linear random(multistochastic process) field generated by identically distributed 2-parameter array of associated random variables. Our result extends the result in Newman and Wright (1982) to the linear 2-parameter processes as well as the result in Kim and Ko (2003) to the 2-parameter case.

ON COMPLETE CONVERGENCE FOR EXTENDED INDEPENDENT RANDOM VARIABLES UNDER SUB-LINEAR EXPECTATIONS

  • Deng, Xin;Wang, Xuejun
    • 대한수학회지
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    • 제57권3호
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    • pp.553-570
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    • 2020
  • In this paper, we establish complete convergence for sequences of extended independent random variables and arrays of rowwise extended independent random variables under sub-linear expectations in Peng's framework. The results obtained in this paper extend the corresponding ones of Baum and Katz [1] and Hu and Taylor [11] from classical probability space to sub-linear expectation space.

ANALYSIS OF A SMOOTHING METHOD FOR SYMMETRIC CONIC LINEAR PROGRAMMING

  • Liu Yong-Jin;Zhang Li-Wei;Wang Yin-He
    • Journal of applied mathematics & informatics
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    • 제22권1_2호
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    • pp.133-148
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    • 2006
  • This paper proposes a smoothing method for symmetric conic linear programming (SCLP). We first characterize the central path conditions for SCLP problems with the help of Chen-Harker-Kanzow-Smale smoothing function. A smoothing-type algorithm is constructed based on this characterization and the global convergence and locally quadratic convergence for the proposed algorithm are demonstrated.