• Journal of KSNVE
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• v.4 no.1
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• pp.71-82
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• 1994

We propose a systematic method to select the master states, which are retained in the reduced model after the order reduction process. The proposed method is based on the fact that the range space of right eigenvector matrix is spanned by orthogonal base vectors, and tries to keep the orthogonality of the submatrix of the base vector matrix as much as possible during the reduction process. To quentify the skewness of that submatrix, we define "Absolute Singularity Factor(ASF)" based on its singular values. While the degree of observability is concerned with estimation error of state vector and up to n'th order derivatives, ASF is related only to the minimum state estimation error. We can use ASF to evaluate the estimation performance of specific partial measurements compared with the best case in which all the state variables are identified based on the full measurements. A heuristic procedure to find suboptimal master states with reduced computational burden is also proposed. proposed.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1E
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• pp.21-27
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• 2005

Environmental mismatch has been one of important issues discussed in matched field processing for underwater source detection problem. To overcome this mismatch many algorithms professing robustness have been suggested. Feature extraction method (FEM) [Seong and Byun, IEEE Journal of Oceanic Engineering, 27(3), 642-652 (2002)] is one of robust matched field processing algorithms, which is based on the eigenvector estimation. Excluding eigenvectors of replica covariance matrix corresponding to large eigenvalues and forming an incoherent subspace of the replica field, the processor is formulated similarly to MUSIC algorithm. In this paper, by using the ocean experimental data, processing results of FEM and MVDR with white noise constraint (WNC) are presented for two levels of multi-tone source. Analysis of eigen-space of CSDM and FEM performance are also presented.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.293-301
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• 2022

Direction of arrival (DOA) estimation of space signals is a basic problem in array signal processing. DOA estimation based on the multiple signal classification (MUSIC) algorithm can theoretically overcome the Rayleigh limit and achieve super resolution. However, owing to its inadequate real-time performance and accuracy in practical engineering applications, its applications are limited. To address this problem, in this study, a DOA estimation algorithm with high parallelism and precision based on an analysis of the characteristics of complex matrix eigenvalue decomposition and the coordinate rotation digital computer (CORDIC) algorithm is proposed. For parallel and single precision, floating-point numbers are used to construct an orthogonal identity matrix. Thus, the efficiency and accuracy of the algorithm are guaranteed. Furthermore, the accuracy and computation of the fixed-point algorithm, double-precision floating-point algorithm, and proposed algorithm are compared. Without increasing complexity, the proposed algorithm can achieve remarkably higher accuracy and efficiency than the fixed-point algorithm and double-precision floating-point calculations, respectively.

• 전자공학회논문지 IE
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• v.45 no.3
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• pp.42-49
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• 2008

This paper proposes a new beamforming algorithm to select beamforming gain or/and diversity gain in CDMA2000, W-CDMA, W-LAN channel according to signal environment on the multipath. In this paper, we present the criteria to obtain deversity gain at any point that based on quantized experimental value. Proposed method proposes represents a performance better than conventional algorithm adopting the largest two eigenvector when angle spread is exit. From the results of performance analysis through various simulation, it is confirmed that proposed method is far superior about $3{\sim}4$ times compare to conventional method in signal environment.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.206-214
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• 2013

This paper proposes a new method for monitoring local voltage stability using the saddle node bifurcation set or loadability boundary in two dimensional power parameter space. The method includes three main steps. First step is to determine the critical buses and the second step is building the static voltage stability boundary or the saddle node bifurcation set. Final step is monitoring the voltage stability through the distance from current operating point to the boundary. Critical buses are defined through the right eigenvector by direct method. The boundary of the static voltage stability region is a quadratic curve that can be obtained by the proposed method that is combining a variation of standard direct method and Thevenin equivalent model of electric power system. And finally the distance is computed through the Euclid norm of normal vector of the boundary at the closest saddle node bifurcation point. The advantage of the proposed method is that it gets the advantages of both methods, the accuracy of the direct method and simple of Thevenin Equivalent model. Thus, the proposed method holds some promises in terms of performing the real-time voltage stability monitoring of power system. Test results of New England 39 bus system are presented to show the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1078-1082
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• 1997

The distance in load parameter space to the closest voltage collapse point provides the worst case power margin and the left eigenvector identifies the most effective direction to steer the system to maximize voltage stability under contingency. This paper presents the results of the comparative performance study of the algorithms, which are applicable to a large scale power system, for computing the closest saddle node bifurcation (CSNB) point. Dobson's iterative method converges with robustness. However the slow process of updating the load increasing direction makes the algorithm less efficient. The direct method converges very quickly. But it diverges if the initial guess is not very close to CSNB. Zeng's method of estimating the approximate critical point in the pre-determined direction is attractive in the sense that it uses only using load flow equations. However, the method is found to be less efficient than Dobson's iterative method. It may be concluded from the above observation that the direct method with the initial values obtained by carrying out the iterative method twice is most efficient at this time and more efficient algorithms are needed for on-line application.

• Structural Engineering and Mechanics
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• v.52 no.5
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• pp.903-918
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• 2014

Large space structures may have resonant low eigenvalues and often these appear with closely-spaced natural frequencies. Owing to the coupling among modes with closely-spaced natural frequencies, each eigenvector corresponding to closely-spaced eigenvalues is ill-conditioned that may cause structural instability. The subspace to an invariant subspace corresponding to closely-spaced eigenvalues is well-conditioned, so a method is presented to design the feedback control law of intelligent structures with closely-spaced eigenvalues in this paper. The main steps are as follows: firstly, the system with closely-spaced eigenvalues is transformed into that with repeated eigenvalues by the spectral decomposition method; secondly, the computation for the linear combination of eigenvectors corresponding to repeated eigenvalues is obtained; thirdly, the feedback control law is designed on the basis of the system with repeated eigenvalues; fourthly, the system with closely-spaced eigenvalues is regarded as perturbed system on the basis of the system with repeated eigenvalues; finally, the feedback control law is applied to the original system, the first order perturbations of eigenvalues are discussed when the parameter modifications of the system are introduced. Numerical examples are given to demonstrate the application of the present method.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.477-491
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• 2021

The Markov modulated Brownian motion is a substantial generalization of the classical Brownian Motion. On the other hand, the Markovian arrival process (MAP) is a point process whose family is dense for any stochastic point process and is used to approximate complex stochastic counting processes. In this paper, we consider a superposition of the Markov modulated Brownian motion (MMBM) and the Markovian arrival process of jumps which are distributed as the bilateral ph-type distribution, the class of which is also dense in the space of distribution functions defined on the whole real line. In the model, we assume that the inter-arrival times of the MAP depend on the underlying Markov process of the MMBM. One of the subjects of this paper is introducing how to obtain the first passage probabilities of the superposed process using a stochastic doubling algorithm designed for getting the minimal solution of a nonsymmetric algebraic Riccatti equation. The other is to provide eigenvalue and eigenvector results on the superposed process to make it possible to apply the GTH-like algorithm, which improves the accuracy of the doubling algorithm.

• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.742-751
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• 2011

This paper presents a robust 3D model hashing dependent on key and parameter by using heat kernel signature (HKS), which is special shape feature descriptor, In the proposed hashing, we calculate HKS coefficients of local and global time scales from eigenvalue and eigenvector of Mesh Laplace operator and cluster pairs of HKS coefficients to 2D square cells and calculate feature coefficients by the distance weights of pairs of HKS coefficients on each cell. Then we generate the binary hash through binarizing the intermediate hash that is the combination of the feature coefficients and the random coefficients. In our experiment, we evaluated the robustness against geometrical and topological attacks and the uniqueness of key and model and also evaluated the model space by estimating the attack intensity that can authenticate 3D model. Experimental results verified that the proposed scheme has more the improved performance than the conventional hashing on the robustness, uniqueness, model space.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.4
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• pp.433-442
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• 2010

In this paper, self-calibration algorithm based on covariance matrix is proposed for compensating amplitude/phase mismatch in multi-baseline interferometer direction finding system. The proposed method is a solution to nonlinear constrained minimization problem which dramatically calibrate mismatch error using space sector concept with cost function as defined in this paper. This method, however, has a drawback that requires an estimated initial angle to determine the proper space sector. It is well known that this type of drawback is common in nonlinear optimization problem. Superior calibration capabilities achieved with this approach are illustrated by simulation experiments in comparison with interferometer algorithm for a varitiety of amplitude/phase mismatch error. Furthermore, this approach has been found to provide an exceptional calibration capabilities even in case amplitude and phase mismatch are more than 30 dB and over $5^{\circ}$, respectively, with sector spacing of less than $50^{\circ}$.