• Journal of applied mathematics & informatics
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• 제25권1_2호
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• pp.345-351
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• 2007

Using more precise majorizing sequences we provide a finer convergence analysis than before [1], [7] of Newton's method in Riemannian manifolds with the following advantages: weaker hypotheses, finer error bounds on the distances involved and a more precise information on the location of the singularity of the vector field.

• Journal of applied mathematics & informatics
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• 제32권5_6호
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• pp.567-584
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• 2014

In this paper, we consider approximation of eigenelements of a two dimensional compact integral operator with a smooth kernel by discrete collocation and iterated discrete collocation methods. By choosing numerical quadrature appropriately, we obtain convergence rates for gap between the spectral subspaces, and also we obtain superconvergence rates for eigenvalues and iterated eigenvectors. We then apply Richardson extrapolation to obtain further improved error bounds for the eigenvalues. Numerical examples are presented to illustrate theoretical estimates.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.337-341
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• 1995

This paper presents a robust control scheme using a multilayer network for the robot manipulator operating under the sea which has large uncertainties such as the buoyancy and the added mass/moment of inertia. The multilayer neural network acts as a compensator of the conventional sliding mode controller to maintain the control performance when the initial assumptions of uncertainty bounds are not valid. By the computer simulation results, the proposed control scheme dose not effectively compensate large uncertainties, but also reduces the steady stare error of the conventional sliding mode controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.172.1-172
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• 2001

In this paper we show the stability analysis of the discrete nonlinear system with average bounded variation of the input. This is the discrete counterpart of that continuous one. We use the Lyapunov stability to prove the boundedness of the steady-state error. Also the allowable maximum variation bounds and the region of attraction are given as the function of the system parameters. Moreover, we prove the uniform convergence for the constant input.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.48.2-48
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• 2002

This paper presents an integrated sliding mode adaptive control scheme for general nonlinear uncertain systems, where structured uncertainty is assumed can be linearly parameterized and unstructured uncertainty is assumed be bounded by unknown constant A certain estimation scheme for this unknown constant is introduced to attenuate the unstructured uncertainty. Presented control scheme is shown to be stable and numerical expressions of bounds of all error signals are given, from which we can acquire some useful information about practical trade-off between tracking performance and parameter estimation property.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제14권4호
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• pp.279-282
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• 2007

Using the center instead of the Lipschitz condition we show how to provide weaker sufficient convergence conditions of the modified Newton Kantorovich method for the solution of nonlinear singular integral equations with Curleman shift (NLSIES). Finer error bounds on the distances involved and a more precise information on the location of the solution are also obtained and under the same computational cost than in [1].

• Communications for Statistical Applications and Methods
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• 제13권1호
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• pp.89-99
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• 2006

This article deals with the problem of estimating parameters of Burr Type XII distribution, on the basis of a general progressive Type II censored sample using Bayesian viewpoints. The maximum likelihood estimator does not admit closed form but explicit sharp lower and upper bounds are provided. Assuming squared error loss and linex loss functions, Bayes estimators of the parameter k, the reliability function, and the failure rate function are obtained in closed form. Finally, a simulation study is also included.

• East Asian mathematical journal
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• 제23권2호
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• pp.257-260
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• 2007

Using the center instead of the Lipschitz condition we show how to provide weaker sufficient convergence conditions of the modified Newton Kantorovich method for the solution of nonlinear singular integral equations with Curleman shift (NLSIES). Finer error bounds on the distances involved and a more precise information on the location of the solution are also obtained and under the same computational cost than in [1].

• Korean Journal of Mathematics
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• 제29권4호
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• pp.687-704
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• 2021

The refinement of an inequality provides better convergence of one quantity towards the other one. We have established the refinements of Hadamard inequalities for Riemann-Liouville fractional integrals via strongly (α, m)-convex functions. In particular, we obtain two refinements of the classical Hadamard inequality. By using some known integral identities we also give refinements of error bounds of some fractional Hadamard inequalities.

• East Asian mathematical journal
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• 제25권4호
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• pp.425-431
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• 2009

We provide a local convergence analysis for Newton-like methods for the solution of generalized equations in a Banach space setting. Using some ideas of ours introduced in [2] for nonlinear equations we show that under weaker hypotheses and computational cost than in [7] a larger convergence radius and finer error bounds on the distances involved can be obtained.