• Bulletin of the Korean Mathematical Society
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• v.50 no.1
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• pp.321-341
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• 2013

In this paper, we discuss the a posteriori error estimates of the semidiscrete mixed finite element methods for quadratic optimal control problems governed by linear hyperbolic equations. The state and the co-state are discretized by the order $k$ Raviart-Thomas mixed finite element spaces and the control is approximated by piecewise polynomials of order $k(k{\geq}0)$. Using mixed elliptic reconstruction method, a posterior $L^{\infty}(L^2)$-error estimates for both the state and the control approximation are derived. Such estimates, which are apparently not available in the literature, are an important step towards developing reliable adaptive mixed finite element approximation schemes for the control problem.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.375-378
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• 1997

This research deals with a problem of reconstructing 3D surface structures from their 2D projections, which is an important research topic in computer vision. In order to provide robust reconstruction algorithm, that is reliable even in the presence of uncertainty in the range images, we first present a detailed model and analysis of several error sources and their effects on measuring three-dimensional surface properties using the space encoded range imaging technique. Our approach has two key elements. The first is the error modeling for the space encoding range sensor and its propagation to the 3D surface reconstruction problem. The second key element in our approach is the algorithm for removing outliers in the range image. Such analyses, to our knowledge, have never attempted before. Experimental results show that our approach is significantly reliable.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.10
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• pp.833-839
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• 2012

In this paper, we analyze the reconstruction error in the modeling of flow field on BFS(Backward Facing Step). In order for the mathematical modelling of a density on the field, the spatial and temporal modes are extracted by POD(Proper Orthogonal Decomposition) method. After formulating the modeling error, we summarize the relationship between the energy strength and the reconstruction errors. Moreover the allowable modeling error limits in the flow control point of view are confined by analysing in the frequency domain as well as time domain of the reconstructed data.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.353-362
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• 1999

This paper presents a shape reconstruction method for automatic inspection of the solder joints on PCBs using X-ray. Shape reconstruction from X-ray radiographic image has been very important since X-ray equipment was used for improving the reliability of inspection result. For this purpose there have been lots of previous works using tomography, which reconstructs the correct shape, laminography or tomosynthesis, which are very fast algorithm. Latter two methods show outstanding performance in cross-sectional image reconstruction of lead type component, but they are also known to show some fatal limitations to some kinds of components such as BGA, because of shadow effect. Although conventional tomography does not have any shadow effect, the shape of PCB prohibits it from being applied to shape reconstruction of solder joints on PCB. This paper shows that tomography using Iterative Reconstruction Technique(IRT) can be applied to this difficult problem without any limitations. This makes conventional radiographic instrument used for shape reconstruction without shadow effect. This means that the new method makes cost down and shadow-free shape reconstruction. To verify the effectiveness of IRT, we develop three dimensional model of BGA solder ball, make projection model to obtain X-ray projection data. and perform a simulation study of shape reconstruction. To compare the performance of IRT with that of conventional laminography or tomosynthesis, reconstruction data are reorganized and error analysis between the original model are also performed.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.9
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• pp.10-16
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• 2011

Interleaving is applied to prevent from exceeding the error-correction capability of channel code. At the receiver, burst errors are converted into random errors after deinterleaving, so the error-correction capability of channel code is not exceeded. However, when a receiver does not have any information on parameters used at an interleaver, interleaving can be seen as an encryption with some pattern. In this case, deinterleaving becomes complicated. In the field of blind deinterleaving, there have recently been a number of researches using linearity of linear block code. In spite of those researches, since the linearity is not applicable to a convolutional code, it is difficult to estimate parameters as in a linear block code. In this paper, we propose a method of blind block deinterleaving using convolutional code reconstruction method.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.266-274
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• 2007

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on top-down machine learning and recursive error back-projection. A face is represented by a linear combination of prototypes of shape and that of texture. With the shape and texture information of each pixel in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those that of texture by solving least square minimizations. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes. In addition, a recursive error back-projection procedure is applied to improve the reconstruction accuracy of high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution images captured at a distance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.578-582
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• 2009

Computer-Generated Hologram (CGH) is generally made by Fourier Transform. CGH is made by an optical reconstruction. Computer-Generated Pseudo Hologram (CGPH) is made up Complex Hadamard Transform instead of CGH which is made by the Fourier Transform. CGPH differs from CGH in point of view the possibility of optical reconstruction. There is an advantage that it cannot be optical reconstruction, in other word, physical leakage of the confidential information is impossible. In this paper, a binary image was converted in Complex Hadamard Transform, and CGPH was made. Improvement of the reconstructed image from CGPH is done by error diffusion method and iterative method. The result that the reconstructed image is improved is shown.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.175-180
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• 2016

The demand for accurate freeform apsheric surface is increasing to satisfy the optical performance. In this paper, we develop the algorithm for opto-mechatronics convergence, that reconstruct the surface 3D profiles from the curvarure data along two orthogonal directions. A synthetic freeform surface with 8.4 m diameter was simulated for the testing. The simulation results show that the reconstruction error is 0.065 nm PV(Peak-to-valley) and 0.013 nm RMS(Root mean square) residual difference. Finally the sensitivity to noise is diagnosed for probe position error, the simulation results proving that the suggested method is robust to position error.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.153-160
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• 2022

A greedy algorithm is proposed to select a subset of nodes of a graph for bandlimited graph signals in which each signal value is generated with its weight. Since graph signals are weighted, we seek to minimize the weighted reconstruction error which is formulated by using the QR factorization and derive an analytic result to find iteratively the node minimizing the weighted reconstruction error, leading to a simplified iterative selection process. Experiments show that the proposed method achieves a significant performance gain for graph signals with weights on various graphs as compared with the previous novel selection techniques.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.258-269
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• 2020

This paper proposes Snapping Shrimp Noise (SSN) detection and corrupted Orthogonal Frequency Division Multiplexing (OFDM) reconstruction methods to increase Bit Error Rate (BER) performance when OFDM transmitted signal is corrupted by impulsive SSNs in underwater acoustic communications. The proposed detection method utilizes multilayer wavelet packet decomposition for detecting impulsive and irregularly concentrated and SSN energy in specific frequency bands of SSN, and the proposed reconstruction scheme uses iterative decision directed-subcarrier reconstruction to recover corrupted OFDM signals using multiple carrier characteristics. Computer simulations were executed to show receiver operating characteristics curve for the detection performance and BER for the reconstruction. The practical ocean experiment of SAVEX 15 demonstrated that the proposed method exhibits a better detection performance compared with conventional detection method and improves BER by 250% and 1230% for uncoded and coded data, respectively, compared with the conventional reconstruction scheme.