• 대한원격탐사학회지
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• 제23권5호
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• pp.455-464
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• 2007

Lee(2007) suggested the Point-Jacobian iteration MAP estimation(PJIMAP) for noise removal of the images that are corrupted by multiplicative speckle noise. It is to find a MAP estimation of noisy-free imagery based on a Bayesian model using the lognormal distribution for image intensity and an MRF for image texture. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. In this study, the MAP estimation is computed by the Point-Jacobian iteration using adaptive parameters. At each iteration, the parameters related to the Bayesian model are adaptively estimated using the updated information. The results of the proposed scheme were compared to them of PJIMAP with SAR simulation data generated by the Monte Carlo method. The experiments demonstrated an improvement in relaxing speckle noise and estimating noise-free intensity by using the adaptive parameters for the Ponit-Jacobian iteration.

• 대한원격탐사학회지
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• 제30권6호
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• pp.817-827
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• 2014

위성 원격 탐사에서는 센서 운영 환경으로 인하여 영상을 수집하는 동안 영상의 질 저하가 일어나며 이러한 영상의 질 저하는 관측된 자료로부터 유용한 정보를 확인하거나 추출하는 데 악 영향을 미치는 번짐 현상(blurring)과 잡음 (noise)을 야기시킨다. 본 연구는 원격 탐사 영상 자료의 질 저하 현상을 모형화하기 위해 Gaussian 가산 잡음과 Markov random field로 정의되는 공간적 연결성을 가정하였다. 그리고 질 저하된 관측 자료로부터 원래 강도의 영상을 복원하기 위한 Point-Jacobian 반복 maximum a posteriori (MAP) 추정 법을 제안한다. 제안 연구는 이웃 창의 형태로 8 개 방향의 창으로 구성된 방사형을 사용하며 각 방향에서의 중심 화소와의 이웃 화소들 간의 Mahalanobis 제곱 거리를 경계 근접성 측정치로 사용한다. 제안 방법의 성능을 평가하기 위해서 고해상도 영상 자료에 나타날 수 있는 다양한 형태의 패턴을 사용하는 simulation 자료를 생성하여 화소 단위 분류 법을 사용하여 정량적 평가를 수행하였고 한반도 안양 북부 지역에서 관측된 1 m 급 IKONOS 자료의 무감독 분할을 통해 정성적 평가를 수행하였다. 실험 결과는 고해상도 원격 탐사 자료 분석에서 제안 영상 복원 법을 적용하면 현저히 분석의 정확성을 높이는 것을 보여 준다.

• Journal of Mechanical Science and Technology
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• 제14권3호
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• pp.272-282
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• 2000

Based on numerical reduced minimization theory, new anisoparametric 3-node elements for out-of-plane curved beam are developed. The elements are designed to be free from spurious constraints. In this paper, the effect of the Jacobian upon numerical solution is analyzed and predicted through reduced minimization analysis of anisoparametric 3-node elements with different Jacobian assumption. The prediction is verified by numerical tests for circular and spiral out-of-plane deformable curved beam models. This paper proposes two kinds of 3-node elements with 7-DOF; one element employs 2-point integration for all strains, and the other element uses 3-point integration with a constant Jacobian within element for calculation of shear strain.

• 한국공작기계학회논문집
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• 제10권3호
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• pp.83-89
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• 2001

In this paper, we discuss the vibration suppression control of spatial redundant flexible manipulators through pseudo-inversed of Jacobian. In order to verify our method, the experiments are performed for PTP(Point To Point) motion of spa-tial flexible manipulators(1) with no redundancy(2) with one redundant DOF(degree of freedom). Finally, a comparison between these results is presented to show the performance of out approach.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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• pp.255-258
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• 2003

In this paper there are different methods used to study the voltage stability, such as the P-V curve method. Jacobian method and the voltage collapse proximity indicator(L-index) method. The P-V curve method is to check operating margin from the maximum operating point. The Jacobian method is to check the eigenvalue or the minimum singular value of the load flow Jacobian matrix. If the power system is unstable, one of the eigenvalues, at least, has crossed the imaginary axis. The L-index method is to quantify how to close a particular operating point. This paper describes these methods to select the best location of FACTS and demonstrate the effectiveness of STATCOM of voltage stability on the IEEE 9-bus system.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1530-1541
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• 2013

The coexistence and extinction of species are important concepts for biological systems and can be distinguished by an investigation of stability. When determining local stability of nonlinear systems, Lyapunov indirect method based on the Jacobian linearization has been widely employed due to its simplicity. Despite such popularity, it is not applicable to singular systems whose Jacobian has at least one eigenvalue that is equal to zero. In such singular cases, an appropriate Lyapunov function should be sought to determine the stability of systems, which is rather difficult and quite involved. In this paper, we seek for a simple criterion to determine stability of the equilibrium that is located at the boundary of the positive orthant, when one of eigenvalues of the Jacobian is zero. The goal of the paper is to present a generalized condition for the equilibrium to attract all trajectories that starting from initial condition in the positive orthant and near the equilibrium. Unlike the Lyapunov direct method, the proposed method requires just a simple algebraic computation for checking the stability of the critical point. Our approach is applied to various biological systems to show the effectiveness of the proposed method.

• 대한원격탐사학회지
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• 제23권1호
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• pp.33-42
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• 2007

In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. MRFs have been used to model spatially correlated and signal-dependent phenomena for SAR speckled images. The MRF is incorporated into digital image analysis by viewing pixel types as slates of molecules in a lattice-like physical system defined on a GRF Because of the MRF-SRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular interactions. The proposed Point-Jacobian Iterative MAP estimation method was first evaluated using simulation data generated by the Monte Carlo method. The methodology was then applied to data acquired by the ESA's ERS satellite on Nonsan area of Korean Peninsula. In the extensive experiments of this study, The proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.124-126
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• 1989

Inverse kinematic problem is a crucial point for robot manipulator control. In this paper, to implement the Jacobian control technique we used the Hopfield(Tank)'s neural network. The states of neurons represent joint veocities, and the connection weights are determined from the current value of the Jacobian matrix. The network energy function is constructed so that its minimum corresponds to the minimum least square error. At each sampling time, connection weights and neuron states are updated according to current joint position. Inverse kinematic solution to the planar redundant manipulator is solved by computer simulation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.207-210
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• 2000

Singular points are those at which the determinant of a Jacobian matrix is zero. A parallel manipulator gains mostly an extra DOF at the singular points, where it can not be properly controlled. In this study, singular points of a cubic parallel manipulator are illustrated by obtaining the determinant of a Jacobian matrix mathematically, and the singular points of the manipulator are found to be three separate planes in a 3D space. The dependency among links for each singular point is determined by applying linear algebra. Also, the singular points and workspace of the cubic parallel manipulator are plotted to check if the workspace contain singular points.

• 제어로봇시스템학회논문지
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• 제5권7호
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• pp.808-813
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• 1999

A fuzzy learning method to control an unstable and multivariable system is presented in this paper, Because the multivariable system has generally a coupling effect between the inputs and outputs, it is difficult to find its modeling equation or parameters. If the system is unstable, initial condition rules are needed to make it stable because learning is nearly impossible. Therefore, this learning method uses the initial rules and introduces a cost function composed of the actual error and error-rate of each output without the modeling equation. To minimize the cost function, we experimentally got the Jacobian matrix in the operating point of the system. From the Jacobian matrix, we can find the direction of the convergence in the learning, and the optimal control rules are finally acquired when the fuzzy rules are updated by changing the portion of the errors and error rates.