• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6A
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• pp.551-557
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• 2011

We investigate lattice-reduction-aided precoding techniques using Look-Up table (LUT) for multi-user multiple-input multiple-output(MIMO) systems. Lattice-reduction-aided vector perturbation (VP) gives large sum capacity with low encoding complexity. Nevertheless lattice-reduction process based on the LLL-Algorithm still requires high computational complexity since it involves several iterations of size reduction and column vector exchange. In this paper, we apply the LUT-aided lattice reduction on VP and propose a scheme to generate the LUT efficiently. Simulation results show that a proposed scheme has similar orthogonality defect and Bit-Error-Rate(BER) even with lower memory size.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.148-155
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• 2006

For the improvement of coding efficiency, the H.264 standard uses new coding tools which are not used in previous coding standards. Among new coding tools, motion estimation using smaller block sizes leads to higher correlation between the motion vectors of neighboring blocks. This characteristic of H.264 is useful for the motion vector recovery. In this paper, we propose the motion vector recovery method based on optical flow. Since the proposed method estimates the optical flow velocity vector from more accurate initial value and optical flow region is limited to 16$\times$16 block size, we can alleviate the complexity of computation of optical flow velocity. Simulation results show that our proposed method gives higher objective and subjective video quality than previous methods.

• The Journal of the Acoustical Society of Korea
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• v.33 no.6
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• pp.400-406
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• 2014

This paper describes a robust watermark decoding model using a SVM(Support Vector Machine). First, the embedding process is performed inversely for a watermarked signal. And then the watermark is extracted using the proposed model. For SVM training of the proposed model, data are generated that are watermarks extracted from sounds containing watermarks by four different embedding schemes. BER(Bit Error Rate) values of the data are utilized to determine a threshold value employed to create training set. To evaluate the robustness, 14 attacks selected in StirMark, SMDI and STEP2000 benchmarking are applied. Consequently, the proposed model outperformed previous method in PSNR(Peak Signal to Noise Ratio) and BER. It is noticeable that the proposed method achieves BER 1% below in the case of PSNR greater than 10 dB.

• ETRI Journal
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• v.36 no.1
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• pp.62-68
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• 2014

This paper presents a novel user selection method based on the signal-to-interference-plus-noise ratio (SINR), which is approximated using limited feedback data at the base stations (BSs) of multiple user multiple-input multiple-output (MU-MIMO) systems. In the proposed system, the codebook vector index, the quantization error obtained from the correlation between the measured channel and the codebook vector, and the measured value of the largest singular value are fed back from each user to the BS. The proposed method not only generates precoding vectors that are orthogonal to the precoding vectors of the previously selected users and are highly correlated with the codebook vector of each user but also adopts the quantization error in approximating the SINR, which eventually provides a significantly more accurate SINR than the conventional SINR-based user selection techniques. Computer simulations show that the proposed method enhances the sum rate of the conventional SINR-based methods by at least 2.4 (2.62) bps/Hz when the number of transmit antennas and number of receive antennas per user terminal is 4 and 1(2), respectively, with 100 candidate users and an SNR of 30 dB.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.3
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• pp.7-17
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• 2018

This paper examines short-run and long-run dynamic relationships between selected macroeconomic variables and stock prices in the Korea Stock Exchange. The data is restricted to the period for which monthly data are available from January 1986 to October 2016 (370 observations) retrieved from the Economic Statistics System database sponsored by the Bank of Korea. The study employs unit root test, cointegration test, vector error correction estimates, impulse response test, and structural break test. The results of the Johansen cointegration test indicate at least three cointegrating equations exist at the 0.05 level in the model, confirming that there is a long-run equilibrium relationship between stock prices and macroeconomic variables in Korea. The results of vector error correction model (VECM) estimates indicate that money supply and short-term interest rate are not related to stock prices in the short-run. However, exchange rate is positively related to stock prices while the industrial production index and inflation are negatively related to stock prices in the short-run. Furthermore, the VECM estimates indicate that the external shock, such as regional and global financial crisis shocks, neither affects changes in the endogenous variables nor causes instability in the cointegrating vector. This study finds that the endogenous variables are determined by their own dynamics in the model.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.7
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• pp.734-740
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• 2003

In this paper, A Vector Modulator based a wideband analog phase shifter is realized with four P-I-N diode attenuators, an asymmetric coupled line coupler, a symmetric coupled line coupler, and a power combiner. Simple configuration to have advantages in cost, size, power, and the number of passive circuits is presented. The phase variation due to phase and amplitude error of a P-I-N diode attenuator is derived and used to optimize the overall circuit. The phase shifter shows a total phase shift of 360$^{\circ}$, a 8.2$^{\circ}$maximum phase error, and a 16${\pm}$2.5 dB insertion loss over the wide frequency range of 1 GHz to 3 GHz.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.120-127
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• 2000

In this paper, we propose multispectral image compression using classified interband prediction and vector quantization in wavelet domain. This method classifies each region considering reflection characteristics of each band in image data. In wavelet domain, we perform the classified intraband VQ to remove intraband redundancy for a reference band image that has the lowest spatial variance and the best correlation with other band. And in wavelet domain, we perform the classifled interband prediction to remove interband redundancy for the remaining bands. Then error wavelet coefficients between original image and predicted image are intraband vector quantized to reduce prediction error. Experiments on remotely sensed satellite image show that coding efficiency of theproposed method is better than that of the conventional method.

• Environmental and Resource Economics Review
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• v.12 no.2
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• pp.327-346
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• 2003

Unlike previous studies on the causal relationship between energy consumption and economic growth, this paper analyses the dynamic causal relationship between these variables using the dynamic vector using Johansen's multiple cointegration procedure, dynamic vector error-correction model and impulse response function. The empirical results show that while the energy consumption to a shock in income responds positively, the income responds positively to the shocks in energy consumption in the first place and then the responses become negative. We also find that the impact of energy consumption shock on the income is short-lived and causes higher inflationary pressure.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.203-211
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• 2010

This study examines a cointegrated vector autoregressive (VAR) model where parameters are subject to switch across the regimes in the term structure of interest rates. To employ the regime switching framework, the Markov-switching vector error correction model (MS-VECM) is allowed to the regime shifts in the vector of intercept terms, the variance-covariance terms, the error correction terms, and the autoregressive coefficient parts. The corresponding approaches are illustrated using the term structure of interest rates in the US Treasury bonds over the period of 1958 to 2009. Throughout the modeling procedure, we find that the MS-VECM can form a statistically adequate representation of the term structure of interest rate in the US Treasury bonds. Moreover, the regime switching effects are analyzed in connection with the historical government monetary policy and with the recent global financial crisis. Finally, the results from the comparisons both in information criteria and in forecasting exercises with and without the regime switching lead us to conclude that the models in the presence of regime dependence are superior to the linear VECM model.