• ETRI Journal
• /
• v.14 no.3
• /
• pp.67-74
• /
• 1992

Discrete variable을 갖는 Mean Field Theory(MFT) neural network은 이미 많은 combinatorial optimization 문제에 적용되어져 왔다. 본 논문에서는 이를 확장하여 continuous variable을 갖는 mean field annealing을 제안하고, 이러한 network에서 integral로 표현되는 spin average를 mean field에 기초하여 어렵지 않게 구할 수 있는 one-variable stochastic simulated annealing을 제안하였다. 이런 방법으로 multi-body problem을 single-body problem으로 바꿀 수 있었다. 또한 이 방법을 이용한 응용으로서 통계학에서 잘 알려진 문제중의 하나인 quantification analysis 문제에 적용하여 타당성을 보였다.

• Bulletin of the Korean Mathematical Society
• /
• v.61 no.2
• /
• pp.489-509
• /
• 2024

In this paper, let q ∈ (0, 1]. We establish the boundedness of intrinsic g-functions from the Hardy-Lorentz spaces with variable exponent H^p(·),q(ℝⁿ) into Lorentz spaces with variable exponent L^p(·),q(ℝⁿ). Then, for any q ∈ (0, 1], via some estimates on a discrete Littlewood-Paley g-function and a Peetre-type maximal function, we obtain several equivalent characterizations of H^p(·),q(ℝⁿ) in terms of wavelets.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.331-336
• /
• 2005

A lot of manufacturing knowledge and method have applied to increase manufacturing efficiency in industry field. DES(Discrete Event Simulation) is one of solution to deal with manufacturing problems in factory. Beginning of research, old maintenance system of KNR ( Korea National Railroad) and its technical problems are basically investigated. KNR has maintained railway vehicle with their own solution based on experience. Very advanced railway vehicles such as KTX (Korea Train Express) and TTX(Tilting Train Express) will be difficult to maintain with their old maintenance method. In order to apply knowledge of DES, maintenance field of railway must be considered. Imaginary maintenance machine are selected to variable of DES. Maintenance capability of each machine will be evaluated base on imaginary data from imaginary machine. The machine could be very expensive as well as difficult to replace. Target of research is minimization of number of machine in railway workshop. So basic knowledge of discrete event simulation is introduced. Then five essential stages of discrete event simulation are provided. Each maintenance case defined as event. Each event is discrete and simulated base on different case such as one maintenance line with one machine and one maintenance line with two machines in railway workshop. simple maintenance method, discrete event simulation, will be come out very powerful in complicate maintenance system and will be helpful to reduce maintenance cost as well as maintenance labor.

• Proceedings of the Optical Society of Korea Conference
• /
• 2001.02a
• /
• pp.62-63
• /
• 2001

We studied a method to use a variable discrete random phase mask in 2-D binary data representation for efficient holographic data storage. The variable phase mask is realized by use of a liquid crystal display.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.4
• /
• pp.463-468
• /
• 2011

Context prediction methods have been developed in two ways - one is a prediction for discrete context and the other is for continuous context. As most of the prediction methods have been used with prediction algorithms in specific domains suitable to the environment and characteristics of contexts, it is difficult to conduct a prediction for a user's context which is based on various environments and characteristics. This study suggests a context prediction method available for both discrete and continuous contexts without being limited to the characteristics of a specific domain or context. For this, we conducted a context prediction based on sequence matching by generating sequences from contexts in consideration of association rules between context attributes and by applying variable weights according to each context attribute. Simulations for discrete and continuous contexts were conducted to evaluate proposed methods and the results showed that the methods produced a similar performance to existing prediction methods with a prediction accuracy of 80.12% in discrete context and 81.43% in continuous context.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.51 no.12
• /
• pp.556-561
• /
• 2002

In this paper, a discrete-time variable structure controller for linear time-varying sampled-data systems with disturbances is proposed. The proposed method guarantees that the system state if globally uniformly ultimately bounded (G.U.U.B), and the ultimate bound is shown to be the order of T, O(T), where T is a sampling period.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.322-326
• /
• 2003

In this paper, we establish a new robust $H_{\infty}$ performance condition for uncertain discrete-time systems with convex polytopic uncertainties. We express the condition as a set of linear matrix inequalities (LMIs), which are used to check stability and $H_{\infty}$ disturbance attenuation level by a parameter-dependent Lyapunov matrix. We show that the new condition provides less conservative result than the existing ones which use single Lyapunov matrix. We also show that the robust $H_{\infty}$ state feedback design problem for such uncertain discrete-time systems can be easily dealt with using the approach. The key point in this paper is to propose a kind of decoupling between the Lyapunov matrix and the system matrices in the parameter-dependent matrix inequality by introducing one new matrix variable.

• 전기의세계
• /
• v.30 no.12
• /
• pp.822-831
• /
• 1981

Many different schemes of the adaptive observer and controller have been developed for both continuous and discrete systems. In this paper we have presented a new scheme of the reduced order adaptive observer for the single input discrete linear time invariant plant. The output equation of the plant, is transformed into the bilinear form in terms of system parameters and the states of the state variable filters. Using the plant output equation the discrete implicit adaptive observer based on the similar philosophy to Nuyan and Carroll is derived and the parameter adaptation algorithm is derived based on the exponentially weighted least square method. The adaptive model following control system is also constructed according to the proposed observer scheme. The proposed observer and controller are rather than simple structure and have a fast adaptive algorithm, so it may be expected that the scheme is suitable to the practical application of control system design. The effectiveness of the algorithm and structure is illustrated by the computer simulation of a third order system. The simulation results show that the convergence speed is proportinal to the increasing of weighting factor alpha, and that the full order and reduced order observer have similar convergence characteristics.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.49 no.3
• /
• pp.26-30
• /
• 2012

This paper presents the observer design method for discrete-time nonlinear systems with delayed output. It is shown that by considering a nonlinear term of error dynamics as an additional state variable, the discrete-time nonlinear error dynamics with time delay can be transformed into the discrete-time linear one with time delay. Sufficient conditions for existence of state observer are characterized by linear matrix inequalities. Finally, an illustrative example is given in order to show the effectiveness of our design method.

• Proceeding of KASS Symposium
• /
• 2005.05a
• /
• pp.236-245
• /
• 2005

This paper was developed the discrete optimum design program by the refined fuzzy-genetic algorithms based on the genetic algorithms and fuzzy theory. The optimum design of this paper can perform both size and shape optimum design for planar and spacial steel structures. In this paper, the objective function is the weight of steel structures and the constraints are the design limits defined by design and buckling strengths, displacements and thicknesses. The design variables are dimensions and coordinates of steel sections. Design examples are given to show the applicability of the discrete optimum design program of this paper.