• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.581-589
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• 1998

An algorithm is proposed for the $L_1$-estimation with linear equality and inequality constraints in linear regression model. The algorithm employs a linear scaling transformation to obtain the optimal solution of linear programming type problem. And a special scheme is used to maintain the feasibility of the updated solution at each iteration. The convergence of the proposed algorithm is proved. In addition, the updating and orthogonal decomposition techniques are employed to improve the computational efficiency and numerical stability.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.367-369
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• 1986

Guaranteed cost control is a method applicable to a class of systems with uncertain parameters that guarantees an upper bound of the cost functional. This paper is concerned with a matrix decomposition technique used to yield a reasonable upper bound of the cost functional for a finite-time LQ regulator problem. The uncertain linear systems dealt with in this paper are described by a set of state equations of single-input phase-variable canonical form which contain unknown but bounded uncertain parameters.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.2
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• pp.14-23
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• 2000

A numerical scheme is proposed to obtain the individual stress intensity factors in an axisymmetric crack and in a three dimensional mixed mode crack. The method is based on the path independence of J and M integral and mutual or two-state conservation integral , which involves two elastic fields. Some numerical example are presented to investigate the effectiveness and applicability of the method for and axisymmetric crack and a three dimensional penny shaped crack problem under mixed mode.

• Journal of Navigation and Port Research
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• v.28 no.4
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• pp.305-309
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• 2004

The problem for parameters estimation of the received signals impinging on array sensors has long been of great research Interest in a great variety of applications, such as radar, sonar, and land mobile communications systems. Conventional subspace-based algorithms, such as MUSIC and ESPRIT, require an extensive computation of inverse matrix and eigen-decomposition In this paper, we propose a new parameters estimation algorithm via nonlinear minimization, which is simplified computationally and estimates signal parameters simultaneously.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.11-13
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• 2010

Combined with the indeterminate boundaries of spatial objects, n:m correspondences makes an object-based matching be a complex problem. In this study, we model the boundary of a polygon object with fuzzy model and describe their overlapping relations as a weighted bipartite graph. Then corresponding pairs including 1:0, 1:1, 1:n and n:m relations are identified using a spectral singular value decomposition.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2956-2958
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• 1999

The classical solution to the noise removal problem is the Wiener filter, which utilizes the second-order statistics of the Fourier decomposition. We discuss a Bayesian formalism which gives rise to a type of wavelet threshold estimation in non-parametric regression. A prior distribution is imposed on the wavelet coefficients of the unknown response function, designed to capture the sparseness of wavelet expansion common to most application. For the prior specified, the posterior median yields a thresholding procedure

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1715-1721
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• 1997

Wavelet transform is not applicable to arbitrarily-shaped region (or object) in images, due to the nature of its global decomposition. In this paper, the arbitrarily-shaped wavelet transform(ASWT) is proposed in order to solve this problem and its properties are investigated. Computation complexity of the ASWT is also examined and it is shown that the ASWT requires significantly fewer computations than conventional wavelet transform, since the ASWT processes only the object region in the original image. Experimental resutls show that any arbitrarily-shaped image segment can be decomposed using the ASWT and perfectly reconstructed using the inverse ASWT.

• Kyungpook Mathematical Journal
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• v.62 no.1
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• pp.107-118
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• 2022

In this note we observe that any truncated multi-index sequence has an interpolating measure supported in Euclidean space. It is well known that the consistency of a truncated moment sequence is equivalent to the existence of an interpolating measure for the sequence. When the moment matrix of a moment sequence is nonsingular, the sequence is naturally consistent; a proper perturbation to a given moment matrix enables us to confirm the existence of an interpolating measure for the moment sequence. We also illustrate how to find an explicit form of an interpolating measure for some cases.

• Journal of Applied and Pure Mathematics
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• v.4 no.5_6
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• pp.287-297
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• 2022

In this paper, we consider a risk-minimization hedging problem for a special European contingent claims. The existence and uniqueness of strategy are given constructively. Firstly, a non-standard European contingent is demonstrated as stochastic payment streams. Then the existence of the risk minimization strategy and also the uniqueness are proved under two kinds market information by using Galtchouk-Kunita-Watanabe decomposition and constructing a 0-achieving strategy risk-minimizing strategies in full information. And further, we have proven risk-minimizing strategies exists and is unique under restrict information by constructing a weakly mean-selffinancing strategy.

• IE interfaces
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• v.13 no.3
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• pp.378-387
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• 2000

As the globalization of manufacturing companies continues, the scope of dependence between these companies and distributors, and other suppliers are growing very rapidly since no one company manufactures or distributes the whole product by themselves. And, the need to increase the efficiency of the whole supply chain is increasing. This paper deals with a multi-plant lot-sizing problem(MPLSP) which happens in a decentralized manufacturing system of a supply chain. In this study, we assume that the whole supply chain is driven by a single source of independent demand and many levels of dependent demands among manufacturing systems in the supply chain. We consider setup cost, transportation cost and time, and inventory holding cost as a decision factor in the MPLSP. The MPLSP is decomposed into two sub-problems: a planning problem of the whole supply chain and a lot-sizing problem of each manufacturing system. The supply chain planning problem becomes a pure linear programming problem and a Generalized Goal Decomposition method is used to solve the problem. Its result is used as a goal of the lot-sizing problem. The lot-sizing problem is solved using the CPLEX package, and then the coefficients of the planning problem are updated reflecting the lot-sizing solution. This procedure is repeated until termination criteria are met. The whole solution process is similar to Lagrangian relaxation method in the sense that the solutions are approaching the optimum in a recursive manner. Through experiments, the proposed closed-loop hierarchical planning and traditional hierarchical planning are compared to optimal solution, and it is shown that the proposed method is a very viable alternative for solving production planning problems of decentralized manufacturing systems and in other areas.