• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2634-2648
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• 2020

In this paper, an adaptive sparse singular value decomposition (ASSVD) algorithm is proposed to estimate the signal matrix when only one data matrix is observed and there is high dimensional white noise, in which we assume that the signal matrix is low-rank and has sparse singular vectors, i.e. it is a simultaneously low-rank and sparse matrix. It is a structured matrix since the non-zero entries are confined on some small blocks. The proposed algorithm estimates the singular values and vectors separable by exploring the structure of singular vectors, in which the recent developments in Random Matrix Theory known as anisotropic Marchenko-Pastur law are used. And then we prove that when the signal is strong in the sense that the signal to noise ratio is above some threshold, our estimator is consistent and outperforms over many state-of-the-art algorithms. Moreover, our estimator is adaptive to the data set and does not require the variance of the noise to be known or estimated. Numerical simulations indicate that ASSVD still works well when the signal matrix is not very sparse.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.785-793
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• 2009

This paper proposes a signature using dominant singular values for video sequence matching. By considering the input image as matrix A, a partition procedure is first performed to separate the matrix into non-overlapping sub-images of a fixed size. The SVD(Singular Value Decomposition) process decomposes matrix A into a singular value-singular vector factorization. As a result, singular values are obtained for each sub-image, then k dominant singular values which are sufficient to discriminate between different images and are robust to image size variation, are chosen and normalized as the signature for each block in an image frame for matching between the reference video clip and the query one. Experimental results show that the proposed video signature has a better performance than ordinal signature in ROC curve.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.115-120
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• 2012

In multi-user multi-input multi-output (MU-MIMO) system, zero forcing beamforming (ZFB) is regarded as a realistic solution for transmitting scheme due to its low complexity and simple structure. However, ZFB shows a significant performance degradation when channel matrix has large condition number. In this case, the largest singular value of the channel inversion matrix has a dominant effect on transmit power. In this paper, we propose a perturbation method for reducing an effect of the dominant singular value. In the proposed algorithm, channel inverse matrix is first decomposed by SVD for the transmit signal to be expressed as a combination of singular vectors. Then, the transmit signal is perturbed to reduce the coefficient of the singular vector corresponding to the largest singular value. When a number of transmit antennas is 4, the simulation results of this paper shows that the proposed method shows 8dB performance enhancement at 10-3 uncoded bit error rate (BER) compared with conventional ZFB. Also, the simulation results show that the proposed method provides a comparable performance to Tomlinson-Harashima Precoding (THP) with much lower complexity.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.9
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• pp.431-438
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• 2001

This paper present experimental results of source identification for non-minimum phase system. Generally, a causal linear system may be described by matrix form. The inverse problem is considered as a matrix inversion. Direct inverse method can\`t be applied for a non-minimum phase system, the reason is that the system has ill-conditioning. Therefore, in this study to execute an effective inversion, SVD inverse technique is introduced. In a Non-minimum phase system, its system matrix may be singular or near-singular and has one more very small singular values. These very small singular values have information about a phase of the system and ill-conditioning. Using this property we could solve the ill-conditioned problem of the system and then verified it for the practical system(cantilever beam). The experimental results show that SVD inverse technique works well for non-minimum phase system.

• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.88-96
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• 2009

In this paper, we present a linear controller for attitude of aircraft. We use a rotational matrix in one approach and a quaternion in the other approach. We also find some interesting mathematical properties concerning a symmetric rotational matrix and we use these properties to analyze the stability of the proposed control law. We find that the quaternion approach is better than rotational matrix approach because there exists no singular region problem in quaternion approach. On the other hand, singular region problem may happens in rotational matrix approach. The controller structure of the quaternion is also very simple compared with the one proposed by using a rotational matrix approach. We make use Matlab Simulink to simulate and illustrate the theoretical claims. The graphic animation program is developed based on Open-GL for the computer simulation of the proposed control algorithm.

• International Journal of Automotive Technology
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• v.2 no.3
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• pp.117-122
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• 2001

For a dynamic analysis of a constrained multibody system, it is necessary to have a routine for satisfying kinematic constraints. LU decomposition scheme, which is used to divide coordinates into dependent and independent coordinates, is efficient but has great difficulty near the singular configuration. Other method such as the projection matrix, which is more stable near a singular configuration, takes longer simulation time due to the large amount of calculation for decomposition. In this paper, the row space and the null space of the Jacobian matrix are proposed by using the pseudo-inverse method and the projection matrix. The equations of the motion of a system are replaced with independent acceleration components using the null space of the Jacobian matrix. Also a new hybrid method is proposed, combining the LU decomposition and the projection matrix. The proposed hybrid method has following advantages. (1) The simulation efficiency is preserved by the LU method during the simulation. (2) The accuracy of the solution is also achieved by the projection method near the singular configuration.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.324-329
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• 2012

Isolation tables are widely used for precision equipments and their isolation performances have been usually expressed and evaluated by transsmissibility. However, transmissibility is a concept for 1-degree of freedom(DOF) system. In practice, isolation tables are supproted by more than 4 springs. Each spring is subjected to vertical and horizontal ground vibrations, and also the table has more than 1-DOF. Therefore, isolation tables should be treated as multi-input/multi-output(MIMO) system of which isolation performance is expressed by transmissibility matrix. However, the matrix is too complicated to be an index for a system. In this paper, maximum singular value of transmissibility matrx is suggested as a simple performance index of a MIMO isolation system. Physical meaning of singular value is explained using a simple a 2-DOF isolation table. Furthermore, maximum singular values of passive, 3-DOF active and 6-DOF active isolation tables are obtained through experiments, and their meaning are explained and compared with each other.

• Journal of the Korea Society of Computer and Information
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• v.23 no.2
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• pp.1-7
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• 2018

The adaptive optics for compensating for optical wavefront distortion due to atmospheric turbulence has recently been used in systems that improve beam quality by eliminating the aberrations of high power laser beam wavefront. However, unseen-mode, which can not be measured in the wavefront sensor, increases the instability of the laser beam wavefront compensator on the adaptive optics system. As a method for improving such instability, a mathematical method for limiting the number of singular values is used when generating the command matrix involved in generation of the drive command of the wavefront compensator. In the past, however, we have relied solely on experimental methods to determine the limiting range of the singular values. In this paper, we propose a criterion for determining the limiting range of the singular values using the driving characteristics and the correlation technique of the wavefront compensator's actuators and have proved its performance experimentally.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.133-138
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• 2006

Singular value decomposition (SDV) approach is applied to the observability analysis of GPS/INS in this paper. A measure of observability for a subspace is introduced. It indicates the minimum size of perturbation in the information matrix that makes the subspace unobservable. It is shown that the measure has direct connections with observability of systems, error covariance, and singular structure of the information matrix. The observability measure given in this paper is applicable to the multi-input/multi-output time-varying systems. An example on the observability analysis of GPS/INS is given. The measure of observability is confirmed to be less sensitive to system model perturbation. It is also shown that the estimation error for the vertical component of gyro bias can be considered unobservable for small initial error covariance for a constant velocity horizontal motion.