• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.703-719
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• 2011

In multi-user wireless communication systems, adaptive modulation and scheduling are promising techniques for increasing the system throughput. However, a mass of wireless recourse will be occupied and spectrum efficiency will be decreased to feedback channel quality indication (CQI) of all users in every subcarrier or chunk for adaptive orthogonal frequency division multiplexing (OFDM) systems. Thus numerous limited feedback schemes are proposed to reduce the system overhead. The recently proposed compressive sensing (CS) theory provides a new framework to jointly measure and compress signals that allows less sampling and storage resources than traditional approaches based on Nyquist sampling. In this paper, we proposed two novel CQI feedback schemes based on general CS and subspace CS, respectively, both of which could be used in a wireless OFDM system. The feedback rate with subspace CS is greatly decreased by exploiting the subspace information of the underlying signal. Simulation results show the effectiveness of the proposed methods, with the same feedback rate, the throughputs with subspace CS outperform the discrete cosine transform (DCT) based method which is usually employed, and the throughputs with general CS outperform DCT when the feedback rate is larger than 0.13 bits/subcarrier.

• 대한기계학회논문집A
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• 제26권9호
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• pp.1822-1830
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• 2002

The paper describes the development of a decomposition based multidisciplinary design optimization (MDO) method that coordinates each of disciplinary subspace optimization (DSO). A multidisciplinary design system considered in the present study is decomposed into a number of subspaces based on their own design objective and constraints associated with engineering discipline. The coupled relations among subspaces are identified by interdisciplinary design variables. Each of subsystem level optimization, that is DSO would be performed in parallel, and the system level coordination is determined by the first order optimal sensitivities of subspace objective functions with respect to interdisciplinary design variables. The central of the present work resides on the formulation of system level coordination strategy and its capability in decomposition based MDO. A fluid-structure coupled design problem is explored as a test-bed to support the proposed MDO method.

• 한국자동차공학회논문집
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• 제11권5호
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• pp.210-218
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• 2003

MDO (multidisciplinary design optimization) technology has been proposed and applied to solve large and complex optimization problems where multiple disciplinaries are involved. In this research. an MDO problem is defined for automobile design which has crashworthiness analyses. Crash model which are consisted of airbag, belt integrated seat (BIS), energy absorbing steering system .and safety belt is selected as a practical example for MDO application to vehicle system. Through disciplinary analysis, vehicle system is decomposed into structure subspace and occupant subspace, and coupling variables are identified. Before subspace optimization, values of coupling variables at given design point must be determined with system analysis. The system analysis in MDO is very important in that the coupling between disciplines can be temporary disconnected through the system analysis. As a result of system analysis, subspace optimizations are independently conducted. However, in vehicle crash, system analysis methods such as Newton method and fixed-point iteration can not be applied to one. Therefore, new system analysis algorithm is developed to apply to crashworthiness. It is conducted for system analysis to determine values of coupling variables. MDO algorithm which is applied to vehicle crash is MDOIS (Multidisciplinary Design Optimization Based on Independent Subspaces). Then, structure and occupant subspaces are independently optimized by using MDOIS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2143-2145
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• 2003

In the linear system identification using the discrete time constant coefficients, there is a subspace method based on 4SID recently much suggested instead of the parametric method like as the maximum likelihood method. The subspace method is not related with the impulse response and difference equation in its input-output equation, but with the system matrix of the direct state space model from the input-output data. The subspace method is a very useful tool to adopt in the multivariable system identification, but it has a shortage unable to adopt in the closed-loop system identification. In this paper, we are suggested the methods to get rid of the shortage of the subspace method in the closed-loop system identification. The subspace method is used in the estimate of the output prediction values from the estimating of the state space vector. And we have compared the results with the outputs of the recursive least square method in the numerical simulation.

• 대한의용생체공학회:의공학회지
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• 제31권6호
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• pp.456-463
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• 2010

In the present study, we proposed a new subspace scanning algorithm to enhance the spatial resolution of electroencephalography (EEG) and magnetoencephalography(MEG) source localization. Subspace scanning algorithms, represented by the multiple signal classification (MUSIC) algorithm and the first principal vector (FINE) algorithm, have been widely used to localize asynchronous multiple dipolar sources in human cerebral cortex. The conventional MUSIC algorithm used principal component analysis (PCA) to extract the noise vector subspace, thereby having difficulty in discriminating two or more closely-spaced cortical sources. The FINE algorithm addressed the problem by using only a part of the noise vector subspace, but there was no golden rule to determine the number of noise vectors. In the present work, we estimated a non-orthogonal signal vector set using independent component analysis (ICA) instead of using PCA and performed the source scanning process in the signal vector subspace, not in the noise vector subspace. Realistic 2D and 3D computer simulations, which compared the spatial resolutions of various algorithms under different noise levels, showed that the proposed ICA-MUSIC algorithm has the highest spatial resolution, suggesting that it can be a useful tool for practical EEG/MEG source localization.

• 대한기계학회논문집A
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• 제25권2호
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• pp.182-191
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• 2001

The paper describes the improvement on concurrent subspace optimization(CSSO) via automatic differentiation. CSSO is an efficient strategy to coupled multidisciplinary design optimization(MDO), wherein the original design problem is non-hierarchically decomposed into a set of smaller, more tractable subspaces. Key elements in CSSO are consisted of global sensitivity equation, subspace optimization, optimum sensitivity analysis, and coordination optimization problem that require frequent use of 1st order derivatives to obtain design sensitivity information. The current version of CSSO adopts automatic differentiation scheme to provide a robust sensitivity solution. Automatic differentiation has numerical effectiveness over finite difference schemes tat require the perturbed finite step size in design variable. ADIFOR(Automatic Differentiation In FORtran) is employed to evaluate sensitivities in the present work. The use of exact function derivatives facilitates to enhance the numerical accuracy during the iterative design process. The paper discusses how much the automatic differentiation based approach contributes design performance, compared with traditional all-in-one(non-decomposed) and finite difference based approaches.

• 전자공학회논문지
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• 제49권9호
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• pp.164-171
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• 2012

센서 어레이(sensor array)가 천이불변(shift invariance) 성질을 가질 때, ESPRIT(Estimation of Signal Parameter via Rotational Invariance Techniques) 방식은 이를 이용하여 어레이에 도래하는 신호의 도래각을 추정한다. 본 논문에서는 ESPRIT 방식을 적용하여 코히런트 신호의 도래각을 효과적으로 추정하는 방법을 제시한다. ESPRIT 방식은 신호부공간(signal subspace)을 이용한다. 코히런트 신호가 존재할 때, 신호부공간을 구하는 방법으로 SS(spatial smoothing) 방식이 널리 알려져 있으나 계산이 매우 복잡하다. 최근에 발표된 CV(correlation vector)에 기초한 방식은 계산은 간단하지만 SS 방식보다 작은 수의 신호를 분해한다. 제안 방식은 상관행렬의 일부를 이용하여 신호부공간을 구성하여 도래각을 추정한다. SS 방식과 비교하여, 제안 방식에서는 분해 가능한 신호의 수는 동일하면서 계산량을 크게 줄일 수 있다.

• 한국통신학회논문지
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• 제29권2C호
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• pp.306-314
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• 2004

배열 안테나를 사용하고 있는 CDMA 기반의 이동 통신 기지국은 효율적인 빔 형성을 위해서 배열 안테나 시스템을 이루고 있는 송수신기 모듈의 정확한 성능을 필요로 하며 이를 위해 오차 보정이 반드시 필요하다. 일반적으로 오차 보정은 internal 오차 보정과 external 오차 보정으로 크게 구분 할 수 있다. 특히 internal 오차 보정은 수신기 모듈을 이루고 있는 RF/IF 회로 소자들의 특성이 변하기 때문에 정기적으로 오차 보정이 필요하다고 알려져 있다. 본 논문에서는 비동기 CDMA 시스템에서 안테나 배열 소자들 간의 진폭 이득과 위상 응답에 오차가 생길 때 온라인으로 보정 할 수 있는 알고리듬을 제안한다. 부공간(subspace) 기반의 알고리듬의 성능 평가와 분석 결과를 제시하기 위해 실험으로 측정한 데이터를 이용하였고, simulated annealing이라는 최적화 방법을 사용하여 부공간(subspace) 기반의 알고리듬에서 발생하는 초기값 문제를 해결하고 모의실험을 통해 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.75.1-75
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• 2002

Several model order reduction methods for large RLC circuits have been developed in the last few years. Krylop subspace based methods are extremely effective for generating the low order models of large system but there is no optimal theory for the resulting models. Alternatively, methods based truncated balanced realization have an optimality property but are too computationally expensive to use on complicated problems such as large RLC circuits. In this paper, we present a method for improving time domain response of reduced order RLC circuits. The method used here is based on combing Krylop subspace based method and truncated balanced realization method plus residualization. The metho...

• 한국통신학회논문지
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• 제37권4A호
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• pp.269-277
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• 2012

원하는 신호의 어레이 응답벡터와 조향벡터사이에 불일치가 있다면 적응 어레이는 원하는 신호와 간섭신호를 동시에 감쇠하기 때문에 심한 성능저하를 가져올 수 있다. 본 논문에서는 조향벡터에 도래각 에러뿐만 아니라 랜덤에러가 있을 때 이에 대처하는 강인한 적응 어레이 기법을 제시한다. 제시된 기법에서는 상관행렬로부터 SIS(signal-plus-interference subspace) 부공간을 구한 후, ULA(uniform linear array) 구조를 이용하여 원하는 신호의 방향벡터 영향을 가능한 줄이면서 간섭 부공간을 추출하고 이에 직교하도록 가중벡터를 구하여 조향벡터 에러에 대한 강인성을 얻는다. 제안된 방식은 DCRCB(doubly constrained robust Capon beamformer) 등 기존방식보다 우수한 SINR(signal-to-interference plus noise ratio) 성능을 가짐을 시뮬레이션 결과는 보여준다.