• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.26-33
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• 2014

For wireless communication systems of (and beyond) LTE-Advanced, multiple-input multiple-output (MIMO) with an increased number of antennas will be utilized for system throughput improvement. When using such an increased number of antenna, an excessive amount of overhead in channel state information (CSI) feedback can be a serious problem. In this paper, we propose methods which reduce the CSI feedback overhead, particularly including application strategies for multi-rank transmission targeted for two or more reception antennas. To reduce the information which is instantaneously transmitted from the reception node to the transmission node, we present a beamforming method utilizing singular value decomposition (SVD) based on channel estimation of partitioned antenna arrays. Since the SVDs for partial matrices of the channel may lose the characteristics of the original unpartitioned matrix, we explain an appropriate scheme to cope with this problem.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.279-286
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• 2006

One of the widely used methods for product recommendation in Internet storefronts is matching product features against target customer profiles. When using this method, it's very important to choose a suitable subset of features for recommendation efficiency and performance, which, however, has not been rigorously researched so far. In this paper, we utilize a dataset collected from a virtual shopping experiment in a Korean Internet book shopping mall to compare several popular methods from other disciplines for selecting features for product recommendation: the vector-space model, TFIDF(Term Frequency-Inverse Document Frequency), the mutual information method, and the singular value decomposition(SVD). The application of SVD showed the best performance in the analysis results.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.99-106
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• 2016

In this paper, we will discuss about correction method of missing data on noisy observation matrix and uncertainty analysis for the potential noise. In situations without missing data in an observation matrix, this solution is known to be accurately induced by SVD (Singular Value Decomposition). However, usually the several entries of observation matrix have not been observed and other entries have been perturbed by the influence of noise. In this case, it is difficult to find the solution as well as cause the 3D reconstruction error. Therefore, in order to minimize the 3D reconstruction error, above all things, it is necessary to correct reliably the missing data under noise distribution and to give a quantitative evaluation for the corrected results. This paper focuses on a method for correcting missing data using geometrical properties between 2D projected object and 3D reconstructed shape and for estimating a noise level of the observation matrix using ranks of SVD in order to quantitatively evaluate the performance of the correction algorithm.

• Korean Circulation Journal
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• v.52 no.8
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• pp.623-631
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• 2022

Background and Objectives: Pulmonary valve replacement (PVR) is the most common operation in adults with congenital heart disease (CHD). There is controversy regarding the best bioprosthesis. We compare the performance of stented bioprosthetic valves (the Mosaic [Medtronic^TM] porcine pericardial against Carpentier Perimount Magna Ease [Edwards^TM] bovine) in pulmonary position in patients with CHD. Methods: Between January 1999 and December 2019, all the PVRs were identified from hospital databases in 2 congenital heart centres in Spain. Valve performance was evaluated using clinical and echocardiographic criteria. Propensity score matching was used to balance the 2 treatment groups. Results: Three hundred nineteen patients were retrospectively identified. After statistical adjustment, 79 propensity-matched pairs were available for comparison Freedom from reintervention for the porcine cohort was 98.3%, 96.1%, and 91.9% at 3, 5, and 10 years and 100%, 98%, and 90.8% for the bovine cohort (p=0.88). Freedom from structural valve degeneration (SVD) for the porcine cohort was 96.9%, 92.8% and 88.7% at 3, 5, and 10 years and 100%, 98%, and 79.1% for the bovine cohort (p=0.38). Bovine prosthesis was associated with a reintervention hazard ratio (HR), 1.12; 95% confidence intervals (CIs), 0.24-5.26; p=0.89 and SVD HR, 1.69 (0.52-5.58); p=0.38. In the first 5 years, there was no difference in outcomes. After 5 years, the recipients of the bovine bioprosthesis were at higher risk for SVD (reintervention HR, 2.08 [0.27-16.0]; p=0.49; SVD HR, 6.99 [1.23-39.8]; p=0.03). Conclusions: Both bioprosthesis have similar outcomes up to 5 years, afterwards, porcine bioprosthesis seem to have less SVD.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1762-1765
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• 1997

Some ill-conditioned processes are very sensitive to small element-wise uncertainties arising in classical element-by-element model identifications. For such processes, accurate identification of simgular values and right singular vectors are more important than theose of the elements themselves. Singular values and right singular vectors can be found by iteraive identification methods which implement the input and output transformations iteratively. Methods based on SVD decomposition, QR decomposition and LU decomposition are proposed and compared with the Kuong and Mac Gregor's method. Convergence proofs are given. These SVD and QR mehtods use normal matrices for the transformations which cannot be calculated analytically in general and so they are hoard to apply to dynamic processes, whereas the LU method used simple analyitc transformations and can be directly applied to dynamic processes.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.10a
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• pp.130-132
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• 2013

This paper presents an improvement for calculating method of astronomical vessel position with circle of equal altitude equation based on using a virtual object in sun and two stars observation. In addition, to enhance the accuracy of ship position achieved from solving linear matrix system, and surmount the disadvantages on rank deficient matrices situation, the authors used singular value decomposition (SVD) in least square method instead of normal equation and QR decomposition, so, the solution of matrix system will be available in all situation. As proposal algorithm, astronomical ship position will give more accuracy than previous methods.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.413-419
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• 1998

A novel order-reduction technique for model predictive control(MPC) is proposed based on the singular value decomposition(SVD) of a pulse response circulant matrix(PRCM) of a concerned system. It is first investigated that the PRCM (in the limit) contains a complete information of the frequency response of a system and its SVD decomposes the information into the respective principal directions at each frequency. This enables us to isolate the significant modes of the system and to devise the proposed order-reduction technique. Though the primary purpose of the proposed technique is to diminish the required computation in MPC, the clear frequency decomposition of the SVD of the PRCM also enables us to improve the robustness through selective excitation of frequency modes. Performance of the proposed technique is illustrated through two numerical examples.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1815-1818
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• 2003

Digital watermarking is technique, which owner's information is inserted in digital image, with intention to protecting a copyright of digital image. In watermarking for copyright and authentication, watermark shouldn't be distorted or disappeared after general image processes like a compression and filtering. In this paper, we present a new digital image watermarking algorithm which combines the discrete wavelet transform (DWT) and the singular value decomposition (SVD). Simulation results show that the newly proposed algorithm is not only robust nevertheless variable attacks like noise, filtering and JPEG compression but also secure in application.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2000-2003
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• 2003

This paper presents a three-dimensional (3D) head pose estimation algorithm for robust face recognition. Given a 3D input image, we automatically extract several important 3D facial feature points based on the facial geometry. To estimate 3D head pose accurately, we propose an Error Compensated-SVD (EC-SVD) algorithm. We estimate the initial 3D head pose of an input image using Singular Value Decomposition (SVD) method, and then perform a Pose refinement procedure in the normalized face space to compensate for the error for each axis. Experimental results show that the proposed method is capable of estimating pose accurately, therefore suitable for 3D face recognition.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.63-70
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• 2008

Narrow-band interference (NBI) from the coexisting narrow-band services affects the performance of ultra wideband (UWB) systems considerably due to the high power of these narrow-band signals with respect to the UWB signals. Specifically, IEEE 802.11a systems which operate around 5 GHz and overlap the band of UWB signals may interfere with UWB systems significantly. In this paper, we suggest a novel NBI suppression technique based on singular value decomposition (SVD) algorithm in time hopping UWB (TH-UWB) systems. SVD is used to approximate the interference which then is subtracted from the received signals. The algorithm precision and closed-form bit error rate (BER) expression are derived in the wireless multipath channel. Comparing with the conventional suppression methods such as a notch filter and a RAKE receiver, the proposed method is simple and robust and especially suitable for UWB systems.