• Title/Summary/Keyword: K-SVD

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Two-Way MIMO AF Relaying Methods Having a Legacy Device without Self-Interference Cancellation (자기간섭 제거 기능이 없는 기존 단말을 가지는 양방향 다중입출력 중계 증폭 전송 기법)

  • Lee, Kyoung-Jae
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.42 no.2
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    • pp.338-344
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    • 2017
  • In this paper, two-way amplify-and-forward relay methods are investigated where two terminals and one relay node are equipped with multiple antennas. In two-way relay channels, it is assumed that one terminal can eliminate its own self-interference but the other cannot. For this channel, we first maximize the sum-rate performance by employing an iterative gradient descent (GD) algorithm. Then, a simple singular value decomposition (SVD) based block triangularization is developed to null the self-interference. Simulation results show the proposed methods outperform the conventional schemes for various environments.

Moving force identification from bending moment responses of bridge

  • Yu, Ling;Chan, Tommy H.T.
    • Structural Engineering and Mechanics
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    • v.14 no.2
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    • pp.151-170
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    • 2002
  • Moving force identification is a very important inverse problem in structural dynamics. Most of the identification methods are eventually converted to a linear algebraic equation set. Different ways to solve the equation set may lead to solutions with completely different levels of accuracy. Based on the measured bending moment responses of the bridge made in laboratory, this paper presented the time domain method (TDM) and frequency-time domain method (FTDM) for identifying the two moving wheel loads of a vehicle moving across a bridge. Directly calculating pseudo-inverse (PI) matrix and using the singular value decomposition (SVD) technique are adopted as means for solving the over-determined system equation in the TDM and FTDM. The effects of bridge and vehicle parameters on the TDM and FTDM are also investigated. Assessment results show that the SVD technique can effectively improve identification accuracy when using the TDM and FTDM, particularly in the case of the FTDM. This improved accuracy makes the TDM and FTDM more feasible and acceptable as methods for moving force identification.

Effect Analysis of Generator Dropping Using Wavelet Singular Value Decomposition (발전기 탈락 시 Wavelet Transform과 Singular Value Decomposition을 이용한 특성 분석)

  • Noh, Chul-Ho;Kim, Won-Ki;Han, Jun;Kim, Chul-Hwan
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.49-50
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    • 2011
  • 본 논문에서는 WT(Wavelet Transform)와 SVD(Singular Value Decomposition)를 함께 사용한 WSVD(Wavelet Singular Value Decomposition)를 이용하여 발전기 탈락 시의 전압 변동 특성을 분석하였다. WSVD 특성 분석을 위해 부산 지역의 345kV급 송전계통을 EMTP-RV로 모델링하였으며, 이 계통모델에서 발전기 탈락을 모의하였다. MATLAB을 통해 이 때 측정된 전압의 WSVD를 계산하여 발전기 탈락에 따른 특성을 분석하였다.

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Feature matching toy Omnidirectional Image based on Singular Value Decomposition

  • Kim, Do-Yoon;Lee, Young-Jin;Myung jin Chung
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.98.2-98
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    • 2002
  • $\textbullet$ Omnidirectional feature matching $\textbullet$ SVD-based matching algorithm $\textbullet$ Using SSD instead of the zero-mean correlation $\textbullet$ The similarity with the Gaussian weighted $\textbullet$ Low computational cost $\textbullet$ It describes the similarity of the matched pairs in omnidirectional images.

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Comparison of Document Clustering Performance Using Various Dimension Reduction Methods (다양한 차원 축소 기법을 적용한 문서 군집화 성능 비교)

  • Cho, Heeryon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.05a
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    • pp.437-438
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    • 2018
  • 문서 군집화 성능을 높이기 위한 한 방법으로 차원 축소를 적용한 문서 벡터로 군집화를 실시하는 방법이 있다. 본 발표에서는 특이값 분해(SVD), 커널 주성분 분석(Kernel PCA), Doc2Vec 등의 차원 축소 기법을, K-평균 군집화(K-means clustering), 계층적 병합 군집화(hierarchical agglomerative clustering), 스펙트럼 군집화(spectral clustering)에 적용하고, 그 성능을 비교해 본다.

The Change of K-MMSE Following Donepezil Medication in Patients with Alzheimer's Disease and Small Vessel Dementia, and the Characteristics of Alzheimer's Disease with Meaningful K-MMSE Change (알쯔하이머병과 소혈관성 치매에서 Donepezil 복용 후 K-MMSE의 변화와 의미 있는 K-MMSE 변화를 보이는 알쯔하이머병 환자의 특징)

  • Kwak, Yong Tae;Han, Il-Woo;Kim, June;Lee, Yu-Sang
    • Korean Journal of Biological Psychiatry
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    • v.12 no.2
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    • pp.98-106
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    • 2005
  • Objectives:Donepezil is a widely used drug for the treatment of patients with Alzheimer's disease(AD). The aim of the present study was to clarify the efficacy and the characteristics of responders to donepezil. Methods:Patients with probable AD(n=80;75.7 years) and small vessel dementia(SVD)(n=18;77.8 years) who received donepezil were retrospectively analyzed using Alzheimer's registry, and three questions were asked:1) Does donepezil therapy improves cognitive symptoms in patients with dementia? 2) If donepezil improves cognitive symptoms, which items of the K-MMSE are improved? 3) What are the characteristics of responder to donepezil medication? Results:1) After donepezil medication, cognitive function measured by the K-MMSE was significantly improved in both types of dementia(AD and SVD), However, statistical differences were not found between these groups. 2) In a clinical trial of donepezil, the patients performed better than before mediation on K-MMSE items assessing orientation, recall, construction, concentration, calculation. 3) In AD, the K-MMSE score before medication was closely related with response of donepezil. Conclusion:This study suggests that donepezil improves various cognitive functions in both types of dementia, and the responsive group had significantly lower K-MMSE scores than the non-responsive group before medication.

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A Study on Comparison of Recommendation Algorithms for Specific Domains (특정 도메인에 적합한 추천 알고리즘 비교에 관한 연구)

  • Lee, HyunChang;Shin, SeongYoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.101-102
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    • 2018
  • 협업 필터링은 데이터 분석을 통한 추천 시스템에서 대표적인 방법이다. 사용 방법은 다양한 아이템에 대해서 사용자들의 평가 데이터를 활용하여 공통적인 패턴을 찾아서 특정 사용자에 대한 선호 아이템을 추천하는 기법이다. 이에 본 논문에서는 여러 가지 알고리즘을 사용하여 지표 측정에 활용하였으며, 사용자 선호에 대한 예측에 적합한 알고리즘을 찾아서 제시하였다.

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A Study on Comparison of Recommendation Algorithms for Specific Domains (특정 도메인에 적합한 추천 알고리즘 비교에 관한 연구)

  • Lee, HyunChang;Shin, SeongYoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.426-427
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    • 2018
  • 협업 필터링은 데이터 분석을 통한 추천 시스템에서 대표적인 방법이다. 사용 방법은 다양한 아이템에 대해서 사용자들의 평가 데이터를 활용하여 공통적인 패턴을 찾아서 특정 사용자에 대한 선호 아이템을 추천하는 기법이다. 이에 본 논문에서는 여러 가지 알고리즘을 사용하여 지표 측정에 활용하였으며, 사용자 선호에 대한 예측에 적합한 알고리즘을 찾아서 제시하였다.

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Time-Varying Multipath Channel Estimation with Superimposed Training in CP-OFDM Systems

  • Yang, Qinghai;Kwak, Kyung-Sup
    • ETRI Journal
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    • v.28 no.6
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    • pp.822-825
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    • 2006
  • Based on superimposed training methods, a novel time-varying multipath channel estimation scheme is proposed for orthogonal frequency division multiplexing systems. We first develop a linear least square channel estimator, and meanwhile find the optimal superimposed sequences with respect to the channel estimates' mean square error. Next, a low-rank approximated channel estimator is obtained by using the singular value decomposition. As demonstrated in simulations, the proposed scheme achieves not only better performance but also higher bandwidth efficiency than the conventional pilot-aided approach.

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Atrial Fibrillation Waveform Extraction Algorithm for Holter Systems (홀터 심전계를 위한 심방세동 신호 추출 알고리즘)

  • Lee, Jeon;Song, Mi-Hye;Lee, Kyoung-Joung
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.49 no.3
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    • pp.38-46
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    • 2012
  • Atrial fibrillation is needed to be detected at paroxysmal stage and to be treated. But, paroxysmal atrial fibrillation ECG is hardly obtained with 12-lead electrocardiographs but Holter systems. Presently, the averaged beat subtraction(ABS) method is solely used to estimate atrial fibrillatory waves even with somewhat large residual error. As an alternative, in this study, we suggested an ESAF(event-synchronous adaptive filter) based algorithm, in which the AF ECG was treated as a primary input and event-synchronous impulse train(ESIT) as a reference. And, ESIT was generated so to be synchronized with the ventricular activity by detecting QRS complex. We tested proposed algorithm with simulated AF ECGs and real AF ECGs. As results, even with low computational cost, this ESAF based algorithm showed better performance than the ABS method and comparable performance to algorithm based on PCA(principal component analysis) or SVD(singular value decomposition). We also proposed an expanded version of ESAF for some AF ECGs with multi-morphologic ventricular activities and this also showed reasonable performance. Ultimately, with Holter systems including our proposed algorithm, atrial activity signal can be precisely estimated in real-time so that it will be possible to calculate atrial fibrillatory rate and to evaluate the effect of anti-arrhythmic drugs.