• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.3
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• pp.248-256
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• 2009

EB(Eigen-Beamforming) has widely been applied to MIMO(Multiple-Input Multiple-Output) systems to form beams which maximize the effective signal-to-interference plus noise ratio(SINR) of the receiver using the singular value decomposition(SVD) of the MIMO channel. However, the signal detection performance for the mobile station near the cell boundary is severely degraded and the transmission efficiency decreases due to the influence of the interference signal from the adjacent cells. In this paper, we propose an adaptive interference mitigation method for the EB transmission, and evaluate the reception performance. In particular, a reception strategy which adaptively utilizes optimal combining(OC) and minimum mean-squared error for Intercell spatial demultiplexing(MMSE-lSD) is proposed, and the reception performance is investigated in terms of the effective SINR and system capacity. For the average system capacity, the proposed adaptive reception demonstrates the performance enhancement compared to the conventional EB reception using the receiver beamforming vector, and up to 2 bps/Hz performance gain is achieved for mobile station located at the cell edge.

• The Journal of the Acoustical Society of Korea
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• v.37 no.5
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• pp.300-308
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• 2018

The contribution analysis of various external aeroacoustic noise sources to interior noise is important, enabling to design an automobile with a low interior noise level. With a new technique, the CD (Cholesky Decomposition), it is proposed to decompose an overall interior noise spectrum into multiple spectra, each representing the contribution of a specific noise source to the interior noise. In order to validate this method, three kinds of experiments were conducted. Furthermore, it is proposed to improve the CD-based contribution analysis method to be integrated with existing exterior microphone arrays in the wind tunnel. This method was validated with an experiment with two speakers.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.47-60
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• 2010

Most of the researches about classification usually have used kNN(k-Nearest Neighbor), SVM(Support Vector Machine), which are known as learn-based model, and Bayesian classifier, NNA(Neural Network Algorithm), which are known as statistics-based methods. However, there are some limitations of space and time when classifying so many web pages in recent internet. Moreover, most studies of classification are using uni-gram feature representation which is not good to represent real meaning of words. In case of Korean web page classification, there are some problems because of korean words property that the words have multiple meanings(polysemy). For these reasons, LSA(Latent Semantic Analysis) is proposed to classify well in these environment(large data set and words' polysemy). LSA uses SVD(Singular Value Decomposition) which decomposes the original term-document matrix to three different matrices and reduces their dimension. From this SVD's work, it is possible to create new low-level semantic space for representing vectors, which can make classification efficient and analyze latent meaning of words or document(or web pages). Although LSA is good at classification, it has some drawbacks in classification. As SVD reduces dimensions of matrix and creates new semantic space, it doesn't consider which dimensions discriminate vectors well but it does consider which dimensions represent vectors well. It is a reason why LSA doesn't improve performance of classification as expectation. In this paper, we propose new LSA which selects optimal dimensions to discriminate and represent vectors well as minimizing drawbacks and improving performance. This method that we propose shows better and more stable performance than other LSAs' in low-dimension space. In addition, we derive more improvement in classification as creating and selecting features by reducing stopwords and weighting specific values to them statistically.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1109-1119
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• 2009

WLAN(Wireless Local Area Network) standard is currently developing with increased wireless internet demand. Though existing IEEE 802.11e demonstrates that data rates exceed 54Mbps with assuring QoS(Quality of Service), wireless internet users can't be satisfied with real communication system. After IEEE 802.11e system, Study trends of IEEE 802.11n show two aspects, enhanced system throughput using aggregation among packets in MAC (Medium Access Control) layer, and better data rates adapting MIMO(Multiple-Input Multiple-Output) in PHY(Physical) layer. But, no one demonstrates IEEE 802.11n system performance results considering MAC and PHY connection. Therefore, this paper adapts MIMO in PHY layer for IEEE 802.11n system based on A-MPDU(Aggregation-MAC Protocol Data Unit) method in MAC layer considering MAC and PHY connection. SVD(Singular Value Decomposition) method with WLAN MIMO TGn Channel is used to analyze MIMO. Consequently, Simulation results show enhanced throughput and data rates compared to existing system. Also, We use Ns-2(Network Simulator-2) considering MAC and PHY connection for reality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1A
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• pp.8-18
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• 2011

Visible light communication (VLC) using optical sources which can be simultaneously utilized for illumination and communication is currently an attractive option for wireless personal area network. Improving the data rate in optical wireless communication system is challenging due to the limited bandwidth of the optical sources. In this paper, we design the singular value decomposition (SVD)-based multiplexing multi-input multi-output (MIMO) system to support two data streams in optical wireless channels. In order to improve the spectral efficiency, the rate adaptation using multi-level pulse amplitude modulation (PAM) is applied according to the channel condition and we propose the method to allocate the optical power, the offset and the size of modulation scheme theoretically under the constraints of the nonnegativity of the modulated signals, the aggregate optical power and the bit error rate (BER) requirement. The simulation results show that the proposed allocation method gives the better performance than the method to allocate the optical power equally for each data stream.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.12
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• pp.56-65
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• 2001

This paper proposes an algorithm for the capacitance extraction of general 3-dimensional conductors in an ideal uniform dielectric that uses a high-order quadrature approximation method combined with the typical first-order collocation method to enhance the accuracy and adopts an efficient matrix-vector product algorithm for the model-order reduction to achieve efficiency. The proposed method enhances the accuracy using the quadrature method for interconnects containing corners and vias that concentrate the charge density. It also achieves the efficiency by reducing the model order using the fact that large parts of system matrices are of numerically low rank. This technique combines an SVD-based algorithm for the compression of rank-deficient matrices and Gram-Schmidt algorithm of a Krylov-subspace iterative technique for the rapid multiplication of matrices. It is shown through the performance evaluation procedure that the combination of these two techniques leads to a more efficient algorithm than Gaussian elimination or other standard iterative schemes within a given error tolerance.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.17-25
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• 2013

In this paper, a coding algorithm is proposed for multi-user multi-input multi-output (MU-MIMO) systems to improve the reception performance in fading conditions without reducing the bandwidth efficiency. The space division multiple access (SDMA) scheme that is one of the commonly used for MU-MIMO systems is vulnerable to the fading. The space time block code (STBC) scheme that is used to overcome the fading has a disadvantage of reduced throughput. The proposed MU-MIMO system first encodes transmitted symbols by linear dispersion code (LDC) which is less vulnerable to the fading and increases the throughput in proportional to the number of transmit antennas. Then, the LDC coded symbols are pre-coded by the result of singular value decomposition (SVD) of the estimated channel gain. We evaluate the performance of the proposed scheme compared with the conventional algorithms by computer simulations.

• Structural Engineering and Mechanics
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• v.65 no.5
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• pp.547-556
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• 2018

Based on the shaking table tests of a 1:3.52 scale one-bay and one-story ancient wooden structure, a simplified structural mechanics model was established, and the structural state equation and observation equation were deduced. Under the action of seismic waves, the damage rule of initial stiffness and yield stiffness of the joint was obtained. The force hammer percussion test and finite element calculations were carried out, and the structural response was obtained. Considering the 5% noise disturbance in the laboratory environment, the stiffness parameters of the mortise-tenon joint were identified by the partial least squares of singular value decomposition (PLS-SVD) and the Extended Kalman filter (EKF) method. The results show that dynamic and static cohesion method, PLS-SVD, and EKF method can be used to identify the damage degree of structures, and the stiffness of the mortise-tenon joints under strong earthquakes is reduced step by step. Using the proposed model, the identified error of the initial stiffness is about 0.58%-1.28%, and the error of the yield stiffness is about 0.44%-1.21%. This method has high accuracy and good applicability for identifying the initial stiffness and yield stiffness of the joints. The identification method and research results can provide a reference for monitoring and evaluating actual engineering structures.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.515-527
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• 2009

IEEE 802.11n is an ongoing next-generation WLAN(Wireless Local Area Network) standard that supports a very high-speed connection with more than 100Mb/s data throughput measured at the MAC(Medium Access Control) layer. Study trends of IEEE 802.11n show two aspects, enhanced data throughput using aggregation among packets in MAC layer, and better data rates adapting MIMO(Multiple-Input Multiple-Output) in PHY(Physical) layer. But, the former doesn't consider wireless channel and the latter doesn't consider aggregation among packets for reality. Therefore, this paper analyzes data throughput for IEEE 802.11n considering MAC and PHY connection. A-MPDU(Aggregation-MAC Protocol Data Unit) and A-MSDU(Aggregation-MAC Service Unit) is adapted considering multi-service in MAC layer, WLAN MIMO TGn channel using SVD(Singular Value Decomposition) is adapted considering MIMO and wireless channel in PHY layer. Consequently, Simulation results shows throughput between A-MPDU and A-MSDU. Also, We use Ns-2(Network simulator-2) for reality.

• The Journal of Information Systems
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• v.27 no.2
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• pp.1-28
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• 2018

Purpose More than 7.6 million mobile apps could be approved on both Apple iTunes Store and Google Play. For managing those existed Apps, Apple Inc. established twenty-four primary categories, as well as Google Play had thirty-three primary categories. However, all of their categorizations have appeared more and more problems in managing and classifying numerous apps, such as app miscategorized, cross-attribution problems, lack of categorization keywords index, etc. The purpose of this study focused on introducing individual information cognitive processing as the classification criteria to update the current categorization on Apple iTunes Store. Meanwhile, we tried to observe the effectiveness of the new criteria from a classification process on Apple iTunes Store. Design/Methodology/Approach A research approach with four research stages were performed and a series of mixed methods was developed to identify the feasibility of adopting individual information cognitive processing as categorization criteria. By using machine-learning techniques with Term Frequency-Inverse Document Frequency and Singular Value Decomposition, keyword lists were extracted. By using the prior research results related to car app's categorization, we developed individual information cognitive processing. Further keywords extracting process from the extracted keyword lists was performed. Findings By TF-IDF and SVD, keyword lists from more than five thousand apps were extracted. Furthermore, we developed individual information cognitive processing that included a categorization teaching process and learning process. Three top three keywords for each category were extracted. By comparing the extracted results with prior studies, the inter-rater reliability for two different methods shows significant reliable, which proved the individual information cognitive processing to be reliable as criteria of categorization on Apple iTunes Store. The updating suggestions for Apple iTunes Store were discussed in this paper and the results of this paper may be useful for app store hosts to improve the current categorizations on app stores as well as increasing the efficiency of app discovering and locating process for both app developers and users.