• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.8-13
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• 2008

In this study, an adaptive node generation procedure in the radial point interpolation method is proposed. Since we set the initial configuration of nodes by subdivision of background cell, abrupt changes of inter-nodal distance between higher and lower error regions are unavoidable. This unpreferable nodal spacing induces additional errors. To obtain the smoothy nodal configuration, it's regenerated by local Delaunay triangulation algorithm This technique was originally developed to generate a set of well-shaped triangles and tetrahedra. To demonstrate the performance of proposed scheme, the results of making optimal nodal configuration with adaptive refinement method are investigated for stress concentration problems.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1551-1558
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• 2013

$H_2$ design of decoupled control systems is treated in the generalized plant model. The existence condition of a decoupling controller is stated and a parameterized form of all achievable decoupled closed loop transfer matrices is presented by using the directional interpolation approaches under the assumption of simple transmission zeros. The class of all decoupling controllers that yield finite cost function is obtained as a parameterized form and an illustrative example to find the optimal controller is provided.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.195-197
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• 2005

In the scalable extension of H.264/AVC, spatial scalability is provided residual information as encoding layered spatial resolution between layers. We use the inter-layer prediction to remove this redundancy. In the inter-layer prediction, as the prediction we can use the signal that is the upsampled signal of the lower resolution layer. In this case, coding efficiency can be different from optimal prediction by kinds of interpolation filter. This paper indicates technique to choose the interpolation filter and to enhance coding efficiency for finding more correct prediction in intra macroblock.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.189-191
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• 2005

In the scalable extension of H.264/AVC, the codec is based on a layered approach to enable spatial scalability. In each layer, the basic concepts of motion compensated prediction and intra prediction are employed as in standard H.264/AVC. Additionally inter-layer prediction algorithm between successive spatial layers is applied to remove redundancy. In the inter-layer prediction, as the prediction we can use the signal that is the upsampled signal of the lower resolution layer. In this case, coding efficiency can be variable as the kinds of interpolation filter. In this paper, we investigate the approach to select the interpolation filter for residual signal in order to optimal prediction.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.1
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• pp.19-26
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• 2011

In this paper, we designed Interpolation FIR(Finite Impulse Response) filter and 1-bit SDM(Sigma- Delta Modulator) for small digital audio speaker, which has low power consumption and high output characteristics. In order to achieve high linearity and low distortion performance of the systems, we adopt Type I Chevychev FIR filter which has equiripple characteristics in the pass band and proposed high efficient FIR filter structure. SDM is the most efficient modulation technique among the noise shaping techniques. In this paper, we implemented SDM using CIFB(Cascade of Intergrators, Feed-Back) which is generally used in DAC of small digital audio speakers. The proposed SDM structure can achieve high SNR, high-efficiency characteristics and low power consumption in mobile devices. Also considering manufacture of SoC(System on Chip), we performed simulation with Matlab and Verilog HDL to obtain optimal number of operational bits and verified a good experimental results.

• Journal of the Korean Mathematical Society
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• v.51 no.2
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• pp.267-288
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• 2014

We propose and analyze two-scale product approximation for semilinear heat equations in the mixed finite element method. In order to efficiently resolve nonlinear algebraic equations resulting from the mixed method for semilinear parabolic problems, we treat the nonlinear terms using some interpolation operator and exploit a two-scale grid algorithm. With this scheme, the nonlinear problem is reduced to a linear problem on a fine scale mesh without losing overall accuracy of the final system. We derive optimal order $L^{\infty}((0, T];L^2({\Omega}))$-error estimates for the relevant variables. Numerical results are presented to support the theory developed in this paper.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.3
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• pp.16-24
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• 1992

In this paper, we solve the problem of designing a robust optimal controller which minimizes the H$\infty$-norm of the mixed sensitivity function matrix for linear multivariable systems. For a given minimized value, ${\gamma}$>o, an algorithm of finding all stabilizing controllers, such that the H$\infty$-norm of the mixed sensitivity function matrix is less than ${\gamma}$, is developed. The proposed algorithm, which is based on the model-matching and the interpolation theory, can be used for the H$\infty$-optimization problem.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.117-126
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• 2023

To improve the overall performance and realism of your game, it is important to calculate the trajectory of a projectile accurately and quickly. One way to increase realism is to use a ballistic model that takes into account factors such as air resistance, density, and wind when calculating a projectile's trajectory. However, the more these factors are taken into account, the more computationally time-consuming and expensive it becomes, creating a trade-off between overall performance and efficiency. Therefore, we present an optimal solution to find a balance between ballistic model accuracy and computation time. We perform ballistic calculations using numerical methods such as Euler, Velocity Verlet, RK2, RK4, and Akima interpolation, and measure and compare the computation time, memory usage (RSS, Resident Set Size), and accuracy of each method. We show developers how to implement more accurate and efficient ballistic models and help them choose the right computational method for their numerical applications.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.140-161
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• 2022

Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.278-286
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• 2007

In this paper, an efficient algorithm is proposed for the interpolation of interlaced images. First of all, by efficiently estimating the directional spatial correlations of neighboring pixels, increased interpolation accuracy can be achieved. And then using the gradient vector which was obtained by Sobel operation, enables to consider the fine directional edges and make it possible to estimate the accurate direction of edges. In other words, it is possible to interpolate the interlaced images with considering the characteristics of images. In addition, by altering the conventional edge detector for the purpose of a easy De-interlacing and multiplying the optimal translation coefficients to each of the gradient vectors, an efficient interpolation for images can be achieved. Comparing with the conventional De-interlacing algorithms, proposed algorithm not only reduced the complexity but also estimated the accurate edge direction and the proposed scheme have been clearly verified that it enhances the objective and subjective image quality by the extensive simulations for various images.