• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.5
• /
• pp.3-12
• /
• 2016

Recently, the study on 5G mobile communication systems using the millimeter-wave frequency band have been actively promoted and the importance of compensation of the nonlinearity of power amplifier caused by the characteristics of millimeter-wave frequency propagation attenuation is increasing. In the paper, we propose a piecewise polynomial model based on subdivision coefficient which are characteristics of power amplifier separated linear section and a non-linear section. In addition, the structure of digital predistortion based on the proposed model and direct learning method are proposed to implement a digital predistortion. To verify the proposed model, digital predistortion based on the proposed model and direct learning method for 60 GHz power amplifier using LTE signal implemented in the FPGA. And the hardware test bench measured performance and complexity. The proposed model achieves 3.3 dB gain over the single polynomial model in terms of the ACLR and reduces 7.5 percent in terms of the complexity.

• Journal of the Korean Magnetic Resonance Society
• /
• v.4 no.2
• /
• pp.116-124
• /
• 2000

Singular value decomposition (SVD) has been used during past few decades in the advanced NMR data processing and in many applicable areas. A new modified SVD, piecewise polynomial truncated SVD (PPTSVD) was developed far the large solvent peak suppression and noise elimination in U signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L$_1$ problems. In TSVD, some unwanted large solvent peaks and noises are suppressed with a certain son threshold value while signal and noise in raw data are resolved and eliminated out in L$_1$ problem routine. The advantage of the current PPTSVD method compared to many SVD methods is to give the better S/N ratio in spectrum, and less time consuming job that can be applicable to multidimensional NMR data processing.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.3
• /
• pp.565-574
• /
• 2004

Classification tree algorithms including as CART by Brieman et al.(1984) in some aspects, recursively partition the data space with the aim of making the distribution of the class variable as pure as within each partition and consist of several steps. SUPPORT(smoothed and unsmoothed piecewise-polynomial regression trees) method of Chaudhuri et al(1994), a weighted averaging technique is used to combine piecewise polynomial fits into a smooth one. We focus on applying SUPPORT to a binary class variable. Logistic model is considered in the caculation techniques and the results are shown good classification rates compared with other methods as CART, QUEST, and CHAID.

• Earthquakes and Structures
• /
• v.2 no.4
• /
• pp.323-336
• /
• 2011

The problem of reconstruction of complete building response from a limited number of response measurements is considered. The response at the intermediate degrees of freedom is reconstructed by using piecewise cubic Hermite polynomial interpolation in time domain. The piecewise cubic Hermite polynomial interpolation is preferred over the spline interpolation due to its trend preserving character. It has been shown that factorization of response data in variable separable form via singular value decomposition can be used to derive the complete set of normal modes of the structural system. The time domain principal components can be used to derive empirical transfer functions from which the natural frequencies of the structural system can be identified by peak-picking technique. A reduced-rank approximation for the system flexibility matrix can be readily constructed from the identified mass-orthonormal mode shapes and natural frequencies.

• KIISE Transactions on Computing Practices
• /
• v.23 no.11
• /
• pp.632-640
• /
• 2017

Although solar insolation is the weather factor with the greatest influence on power generation in photovoltaic systems, the Meterological Agency does not provide solar insolation data for future dates. Therefore, it is essential to research prediction methods for solar insolation to efficiently manage photovoltaic systems. In this study, we propose a Dynamic Piecewise Prediction Model that can be used to predict solar insolation values for future dates based on information from the weather forecast. To improve the predictive accuracy, we dynamically divide the entire data set based on the sun altitude and cloudiness at the time of prediction. The Dynamic Piecewise Prediction Model is developed by applying a polynomial linear regression algorithm on the divided data set. To verify the performance of our proposed model, we compared our model to previous approaches. The result of the comparison shows that the proposed model is superior to previous approaches in that it produces a lower prediction error.

• Journal of Multimedia Information System
• /
• v.5 no.1
• /
• pp.63-66
• /
• 2018

In this work, the smoothing and the interpolation basis splines are analyzed. As well as the possibility of using the spectral properties of the basis splines for digital signal processing are shown. This takes into account the fact that basic splines represent finite, piecewise polynomial functions defined on compact media.

• Journal of the Korean Geosynthetics Society
• /
• v.15 no.1
• /
• pp.1-10
• /
• 2016

Recently, offshore wind farms are increasingly expected, because there are huge resource and large site in offshore. Jeju island has optimum condition for constructing a wind energy farm. Unlike the mainland, Jeju island has stratified structure distribution between rock layers sediments due to volcanic activation. In these case, it can be occur engineering problems in whole structures as well as the safety of foundation as the thickness and distribution of sediment under top rock layer can not support sufficiently the structure. In this study, field lateral load test of the pile for analyzing lateral behavior of the offshore wind turbine which is embedded in basalt. After calculating the subgrade resistance and the horizontal deflection from the measured strain to derive p-y curve from the lateral load test results, the subgrade resistance amplifies the error in the process of differentiation and the error of piecewise polynomial curve fitting is the smallest. In order to calculate the horizontal deflection from the measured strain, the six-order polynomial was used.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.1
• /
• pp.39-47
• /
• 2014

In this study, the epipolar images were created by both methods of resolution adjustment and piecewise approach using RPC(Rational Polynomial coefficients) and ancillary data of IKONOS-2 and SPOT-5 satellite images whose resolutions are different from each other. The stereo geometry of these two satellite images was analyzed and the RPC block modelling was accomplished for generating epipolar images. In order to evaluate the accuracy of created epipolar images, the y-parallaxes were analyzed for the specific points which were apparently identified in mountainous, plain and urban area. Also the RMSEs of the specific points were calculated using the coordinates from the epipolar stereo images and the coordinates from the block triangulation. Y-parallaxes were within one pixel and the RMSEs were within two meters for X, Y and Z each.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.17 no.4
• /
• pp.156-166
• /
• 2014

As of 2014, KARI (Korea Aerospace Research Institute) operates two high-resolution satellites such as Kompsat-2 and Kompsat-3. Kompsat-3 has capability of in-track stereo images acquisition but it is quite limited because the stereo mode lowers the spatial coverage in a trajectory. In this paper we analyze the epipolar geometry from the heterogeneous Kompsat-2 and Kompsat-3 image combination to epipolar resample them for 3D spatial data acquisition. The analysis was carried out using the piecewise approach with RPCs (Rational Polynomial Coefficients) and the result showed the parabolic epipolar curve pattern. We also concluded that the third order polynomial transformation is required for epipolar image resampling. The resampled image pair showed 1 pixel level of y-parallax and can be used for 3D display and digitizing.

• Communications for Statistical Applications and Methods
• /
• v.19 no.2
• /
• pp.293-301
• /
• 2012

Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.