• 충청수학회지
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• 제24권4호
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• pp.883-893
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• 2011

In this paper we study h-stability of the solutions of nonlinear difference system via the notion of $n_{\infty}$-summable similarity between its variational systems. Also, we show that two concepts of h-stability and h-stability in variation for nonlinear difference systems are equivalent. Furthermore, we characterize h-stability for nonlinear difference systems by using Lyapunov functions.

• 충청수학회지
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• 제24권1호
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• pp.105-112
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• 2011

In this paper, we investigate h-stability of the nonlinear perturbed difference system by using comparison principle.

• 대한수학회보
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• 제38권1호
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• pp.101-111
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• 2001

We investigate the property of h-stability, which is an important extension of the notions of exponential stability and uniform Lipschitz stability in variation for nonlinear Volterra difference systems.

• 대한수학회보
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• 제50권5호
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• pp.1555-1565
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• 2013

In this paper, some new generalized discrete Halanay inequalities are established. On the basis of these new established inequalities, we obtain the attracting set and the global asymptotic stability of the nonlinear discrete systems. Our results established here extend the main results in [R. P. Agarwal, Y. H. Kim, and S. K. Sen, New discrete Halanay inequalities: stability of difference equations, Commun. Appl. Anal. 12 (2008), no. 1, 83-90] and [S. Udpin and P. Niamsup, New discrete type inequalities and global stability of nonlinear difference equations, Appl. Math. Lett. 22 (2009), no. 6, 856-859].

• 전기학회논문지
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• 제59권6호
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• pp.1159-1166
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• 2010

To improve prediction quality of a nonlinear prediction system, the system's capability for uncertainty of nonlinear data should be satisfactory. This paper presents a TSK fuzzy prediction system that can consider and deal with the uncertainty of nonlinear data sufficiently. In the design procedures of the proposed system, HCBKA(Hierarchical Correlationship-Based K-means clustering Algorithm) was used to generate the accurate fuzzy rule base that can control output according to input efficiently, and the first-order difference method was applied to reflect various characteristics of the nonlinear data. Also, multiple prediction systems were designed to analyze the prediction tendencies of each difference data generated by the difference method. In addition, to enhance the prediction quality of the proposed system, an error compensation method was proposed and it compensated the prediction error of the systems suitably. Finally, the prediction performance of the proposed system was verified by simulating two typical time series examples.

• 대한수학회보
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• 제56권4호
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• pp.977-992
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• 2019

Mittag-Leffler stability of nonlinear fractional nabla difference systems is defined and the Lyapunov direct method is employed to provide sufficient conditions for Mittag-Leffler stability of, and in some cases the stability of, the zero solution of a system nonlinear fractional nabla difference equations. For this purpose, we obtain several properties of the exponential and one parameter Mittag-Leffler functions of fractional nabla calculus. Two examples are provided to illustrate the applicability of established results.

• 충청수학회지
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• 제22권3호
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• pp.535-543
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• 2009

We investigate h-stability of solutions of nonlinear Volterra difference systems and linear Volterra difference systems.

• 대한수학회보
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• 제41권3호
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• pp.435-450
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• 2004

We show that two concepts of h-stability and h-stability in variation for nonlinear difference systems are equivalent by using the concept of $n_{\infty}$-summable similarity of their associated variational systems. Also, we study h-stability for perturbed non-linear system y(n+1) =f(n,y(n)) + g(n,y(n), Sy(n)) of nonlinear difference system x(n+1) =f(n,x(n)) using the comparison principle and extended discrete Bihari-type inequality.

• Journal of applied mathematics & informatics
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• 제31권1_2호
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• pp.277-284
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• 2013

In this paper, we investigate $h$-stability of the nonlinear perturbed difference system via $n_{\infty}$-similarity.

• 대한수학회보
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• 제44권1호
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• pp.177-184
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• 2007

We study the asymptotic behavior of nonlinear Volterra difference system $$x(n+1)=f(n,x(n))+{\sum\limits^{n}_{s=n_{o}}\;g(n,s,x(s)),\;x(n_{o})=xo$$ by using the resolvent matrix R(n, m) of the corresponding linear Volterra system and the comparison principle.