• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1854-1863
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• 2003

In the recent digital communication systems, the performance of Turbo Code using the mr correction coding depends on the interleaver influencing the free distance determination and the recursive decoding algorithms that is executed in the huh decoder. However, performance depends on the interleaver depth that needs many delays over the reception process. Moreover, turbo code has been blown as the robust coding methods with the confidence over the fading channel. International Telecommunication Union(ITU) has recently adopted it as the standardization of the channel coding over the third generation mobile communications(IMT­2000). Therefore, in this paper, we preposed the interleaver that has the better performance than existing block interleaver, and modified turbo decoder that has the parallel concatenated structure using MAP algorithm. In the real­time voice and video service over third generation mobile communications, the performance of the proposed two methods was analyzed and compared with the existing methods by computer simulation in terms of reduced decoding delay using the variable decoding method over AWGN and fading channels for CDMA environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1792-1801
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• 2012

Symbol timing error amounts to a major degradation in the system performance. Conventionally, timing error is estimated by predefined preamble on both transmitter and receiver. The maximum of the correlation result is considered the start of the OFDM symbol. Problem arises when the prime path is not the strongest one. In this paper, we propose a new combined time and channel estimation method for multi-band OFDM ultra wide-band (MB-OFDM UWB) systems. It is assumed that a coarse timing has been obtained at a stage before the proposed scheme. Based on the coarse timing, search interval is set (or time candidates). Exploiting channel statistics that are assumed to be known by the receiver, we derive a maximum a posteriori estimate (MAP) of the channel impulse response. Based on this estimate, we discern for the timing error. Timing estimation performance is compared with the least squares (LS) channel estimate in terms of mean squared error (MSE). It is shown that the proposed timing scheme is lower in MSE than the LS method.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.3 no.2
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• pp.65-71
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• 2017

To assess the effects of filter and reconstruction of Cu-64 PET data on Siemens scanner, the various reconstruction algorithm with various filters were assessed in terms of spatial resolution, non-uniformity (NU), recovery coefficient (RC), and spillover ratio (SOR). Image reconstruction was performed using filtered backprojection (FBP), 2D ordered subset expectation maximization (OSEM), 3D reprojection algorithm (3DRP), and maximum a posteriori algorithms (MAP). For the FBP reconstruction, ramp, butterworth, hamming, hanning, or parzen filters were used. Attenuation or scatter correction were performed to assess the effect of attenuation and scatter correction. Regarding spatial resolution, highest achievable volumetric resolution was $3.08mm^3$ at the center of FOV when MAP (${\beta}=0.1$) reconstruction method was used. SOR was below 4% for FBP when ramp, Hamming, Hanning, or Shepp-logan filter were used. The lowest NU (highest uniform) after attenuation & scatter correction was 5.39% when FBP (parzen filter) was used. Regarding RC, 0.9 < RC < 1.1 was obtained when OSEM (iteration: 10) was used when attenuation and scatter correction were applied. In this study, image quality of Cu-64 on Siemens Inveon PET was investigated. This data will helpful for the quantification of Cu-64 PET data.

• Geotechnical Engineering
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• v.10 no.1
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• pp.47-62
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• 1994

It has been well known that the rainfall-triggered rise of groundwater levels is one of the most important factors resulting the instability of the hillside slopes. Thus, the prediction of porewater pressure is an essential step in the evaluation of landslide hazard. This study involves the development and verification of numerical groundwater flow model for the prediction of groundwater flow fluctuations accounting for both of unsatu나toed flow and saturated flow on steep hillside slopes. The first part of this study is to develop a nomerical groundwater flow model. The numerical technique chosen for this study is the finitro element method in combination with the finite difference method. The finite element method is used to transform the space derivatives and the finite difference method is used to discretize the time domain. The second part of this study is to estimate the unknown model parameters used in the proposed numerical model. There were three parameters to be estimated from input -output record $K_e$, $\psi_e$, b. The Maximum -A-Posteriori(MAP) optimization method is utilized for this purpose, . The developed model is applied to a site in Korea where two debris avalanches of large scale and many landslides of small scale were occurred. The results of example analysis show that the numerical groundwater flow model has a capacity of predicting the fluctuation of groundwater levels due to rainfall reasonably well.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.345-354
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method has proven to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper, we applied the super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and are overlapped at high rate. We constructed the observation model between the HR images and LR images applied with the Maximum A Posteriori(MAP) reconstruction method which is one of the major methods in the super resolution grid construction. Based on the MAP method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.16-22
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• 2012

In this paper, we proposed a method of baseline correction for analysis of Raman spectra of platelets from Alzheimer's disease (AD) transgenic mice. Measured Raman spectra include the meaningful information and unnecessary noise which is composed of baseline and additive noise. The Raman spectrum is divided into the local region including several peaks and the spectrum of the region is modeled by curve fitting using Gaussian model. The additive noise is clearly removed from the process of replacing the original spectrum with the fitted model. The baseline correction after interpolating the local minima of the fitted model with linear, piecewise cubic Hermite and cubic spline algorithm. The baseline corrected models extract the feature with principal component analysis (PCA). The classification result of support vector machine (SVM) and maximum $a$ posteriori probability (MAP) using linear interpolation method showed the good performance about overall number of principal components, especially SVM gave the best performance which is about 97.3% true classification average rate in case of piecewise cubic Hermite algorithm and 5 principal components. In addition, it confirmed that the proposed baseline correction method compared with the previous research result could be effectively applied in the analysis of the Raman spectra of platelet.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.21-26
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• 2011

Feature ranking is useful to gain knowledge of data and identify relevant features. In this study, we proposed a use of feature ranking for classification of neuro-degeneration and vascular dementia in micro-Raman spectra of platelet. The entire region of the spectrum is divided into local region including several peaks, followed by Gaussian curve fitting method in the region to be modeled. Local minima select from the subregion and then remove the background based on the position by using interpolation method. After preprocessing steps, significant features were selected by feature ranking method to improve the classification accuracy and the computational complexity of classification system. PCA (principal component analysis) transform the selected features and the overall features that is used classification with the number of principal components. These were classified as MAP (maximum a posteriori) and it compared with classification result using overall features. In all experiments, the computational complexity of the classification system was remarkably reduced and the classification accuracy was partially increased. Particularly, the proposed method increased the classification accuracy in the experiment classifying the Parkinson's disease and normal with the average 1.7 %. From the result, it confirmed that proposed method could be efficiently used in the classification system of the neuro-degenerative disease and vascular dementia of platelet.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.5
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• pp.39-48
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• 2009

Many super-resolution reconstruction algorithms have been proposed since it was the first proposed in 1984. The spatial domain approach of the super-resolution reconstruction methods is accomplished by mapping the low resolution image pixels into the high resolution image pixels. Generally, a super-resolution reconstruction algorithm by using the spatial domain approach has the noise problem because the low resolution images have different noise component, different PSF, and distortion, etc. In this paper, we proposed the new super-resolution reconstruction method that uses the L1 norm to minimize noise source and also uses the Huber norm to preserve edges of image. The proposed algorithm obtained the higher image quality of the result high resolution image comparing with other algorithms by experiment.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.211-221
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• 1998

It is becoming apparent that stereo matching algorithms need much information from high level cognitive processes. Otherwise, conventional algorithms based on bottom-up control alone are susceptible to local minima. We introduce a system that consists of two levels. A lower level, using a usual matching method, is based upon the local neighborhood and a second level, that can integrate the partial information, is aimed at contextual matching. Conceptually, the introduction of bottom-up and top-down feedback loop to the usual matching algorithm improves the overall performance. For this purpose, we model the image attributes using a Markov random field (MRF) and thereupon derive a maximum a posteriori (MAP) estimate. The energy equation, corresponding to the estimate, efficiently represents the natural constraints such as occlusion and the partial informations from the other levels. In addition to recognition, we derive a training method that can determine the system informations from the other levels. In addition to recognition, we derive a training method that can determine the system parameters automatically. As an experiment, we test the algorithms using random dot stereograms (RDS) as well as natural scenes. It is proven that the overall recognition error is drastically reduced by the introduction of contextual matching.

• Journal of electromagnetic engineering and science
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• v.6 no.3
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• pp.147-154
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• 2006

In this paper, we propose and present implementation results of a high-speed turbo decoding algorithm. The latency caused by (de) interleaving and iterative decoding in a conventional maximum a posteriori(MAP) turbo decoder can be dramatically reduced with the proposed design. The source of the latency reduction is come from the combination of the radix-4, dual-path processing, parallel decoding, and rearly-stop algorithms. This reduced latency enables the use of the turbo decoder as a forward error correction scheme in real-time wireless communication services. The proposed scheme results in a slight degradation in bit-error rate(BER) performance for large block sizes because the effective interleaver size in a radix-4 implementation is reduced to half, relative to the conventional method. Fixed on the parameters of N=212, iteration=3, 8-states, 3 iterations, and QPSK modulation scheme, we designed the adaptive high-speed turbo decoder using the Xilinx chip (VIRTEX2P (XC2VP30-5FG676)) with the speed of 17.78 Mb/s. From the results, we confirmed that the decoding speed of the proposed decoder is faster than conventional algorithms by 8 times.