• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.6
• /
• pp.63-74
• /
• 2007

Fast Fourier transform(FFT) is powerful, fast computation framework for convolution in many image restoration application. However, an actually observed image acquired with finite aperture of the acquisition device from the infinite background and it lost data outside the cropped region. Because of these the boundary artifacts are produced. This paper reviewed and summarized the up to date the techniques that have been applied to reduce of the boundary artifacts. Moreover, we propose a new block-based fast image restoration using combined extrapolation and edge-tapering without boundary artifacts with reduced computational loads. We apply edgetapering to the inner blocks because they contain outside information of boundary. And outer blocks use half-convolution extrapolation. For this process it is possible that fast image restoration without boundary artifacts.

• Nuclear Engineering and Technology
• /
• v.50 no.7
• /
• pp.1051-1059
• /
• 2018

Fast periodic pulsed reactor is a type of reactor in which the fission bursts are formed entirely with external reactivity modulation with a specified time periodicity. This type of reactors could generate much larger intensity of neutron beams for experimental use, compared with the steady state reactors. In the design of fast periodic pulsed reactors, the time dependent simulation of the power pulse is majorly based on a point kinetic model, which is known to have limitations. A more accurate calculation method is desired for the design analyses of fast periodic pulsed reactors. Monte Carlo computer code MCNP6 is used for this task due to its three dimensional transport capability with a continuous energy library. Some new routines were added to simulate the rotation of the movable reflector parts in the time dependent calculation. Fast periodic pulsed reactor IBR-2M was utilized to validate the new routines. This reactor is periodically in prompt supercritical state, which lasts for ${\sim}400{\mu}s$, during the equilibrium state. This generates long neutron fission chains, which requires tremendously large amount of computation time during Monte Carlo simulations. Russian Roulette was applied for these very long neutron chains in MCNP6 calculation, combined with other approaches to improve the efficiency of the simulations. In the power pulse of the IBR-2M at equilibrium state, there is some discrepancy between the experimental measurements and the calculated results using the point kinetics model. MCNP6 results matches better the experimental measurements, which shows the merit of using MCNP6 calculation relative to the point kinetics model.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.145-148
• /
• 2001

This paper presents a phase-based stereo matching algorithm in order to efficiently extract 3-dimensional objects from two 2D images. Conventional phase-based methods, especially using windowed Fourier phases, inherit good properties in the cage of hierarchical approaches, because they basically use a multi-resolution phase map. On the contrary, their computational cost is too heavy. Therefore, a fast hierarchical approach, using multi-resolution phase-based strategy and reducing redundancies of phase calculations based on FFT concept is proposed in this paper. In addition, a structural matching algorithm on the phase domain is presented to improve the matching quality. In experimental results. it is shown that the computation loads are considerably reduced about 8 times and stable outputs are obtained from various images.

• Proceedings of the IEEK Conference
• /
• 2000.11d
• /
• pp.199-202
• /
• 2000

Speaking Rate has variety depends on the situation and habit of speakers. It has been many studied about speaking rate In speaker recognition. The study of speaking rate in speech recognition is one of considerable matter when It is recognized the speakers and it is measured by many speech data base and complicate estimation for accuracy. In this paper, conventional vocoder process the speech signal when encoding and transmitting without regard to speaking rate so in order to apply the speaking rate for vocoder It should be considered the simpler algorithm and less computation amount than the conventional method of speaking rate used In speech recognition. We proposed the speaking rate algorithm which is used the simple parameter with Line Spectrum Pair (LSP). The proposed peaking rate method is measured by the information of LSP in speech. We measured the variety rate of phenomenon about utterances which have different velocity, respectively. As a result, It has distinct variation rate of phenomenon between utterances uttered fast and slow and the rate is 42.8% higher in case of uttered fast than in case of uttered slow.

• Communications for Statistical Applications and Methods
• /
• v.22 no.6
• /
• pp.665-674
• /
• 2015

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.623-628
• /
• 2008

We present a new method of extracting foreground object from background image for vision-based game interface. Background Subtraction is an important preprocessing step for extracting the features of tracking objects. The image is divided into the cells where the Local Histogram with Gaussian kernel is computed and compared with the corresponding one using Bhattacharyya distance measure. The histogram-based method is partially robust against illumination change, noise and small moving objects in background. We propose a Multi-Scaled Integral Histogram approach for noise suppression and fast computation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1997.04a
• /
• pp.62-67
• /
• 1997

This paper reprdsents a new scheme of neural network control system analysis the robustues of robot manipulator using digital signal processors. Digtal signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In additions, DSPs are a s fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Durng past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. The proposed neuro network control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.7
• /
• pp.865-870
• /
• 2018

A machine vision based industrial inspection includes defects detection and classification. Fast inspection is a fundamental problem for many applications of real-time vision systems. It requires little computation time and localizing defects robustly with high accuracy. Deep learning technique have been known not to be suitable for real-time applications. Recently a couple of fast region-based CNN algorithms for object detection are introduced, such as Faster R-CNN, and YOLOv2. We apply these methods for an industrial inspection problem. Three CNN based detection algorithms, VOV based CNN, Faster R-CNN, and YOLOv2, are experimented for defect detection on metal surface. The results for inspection time and various performance indices are compared and analysed.

• 한국전산유체공학회:학술대회논문집
• /
• 2001.10a
• /
• pp.58-62
• /
• 2001

Aparallel computing environment was constructed based on Windows 2000 operating system. This cluster was configured using Fast-Ethernet system to hold up together the clients within a network domain. For the parallel computation, MPI implements for Windows such as MPICH.NT.1.2.2 and MP-MPICHNT.1.2 were used with Compaq Visual Fortran compiler which produce a well optimized executives for x86 systems. The evaluation of this cluster performance was carried out using a preconditioned Navier-Stokes code for the 2D analysis of a compressible and viscous flow around a compressor blade. The parallel performance was examined in comparison with those of Linux clusters studied previously by changing a number of processors, problem size and MPI libraries. The result from the test problems presents that parallel performance of the low cost Fast-Ethernet Windows cluster is superior to that of a Linux cluster of similar configuration and is comparable to that of a Myrinet cluster.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.1
• /
• pp.102-109
• /
• 2001

In this paper, in order to reduce the computational complexity of codebook, we propose a fast search algorithm which takes advantage of the information generated in the process of the self-organizing map (SOM). In an attempt to demonstrate the influence of the ordering of codebook on the performance of the partial distance search (PDS), we present the results of computation savings for three cases of ordering of codebooks.