• 한국통신학회논문지
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• 제32권4C호
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• pp.440-446
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• 2007

본 논문은 엘레멘트 인버스 처리에 근거한 재킷 변환을 통한 DFT 행렬의 새로운 표현을 다룬다. DFT 행렬의 역을 단지 재킷 변환의 소행렬 분해에 따라 표현하며 이러한 결과는 DFT 행렬의 역이 단지 이의 희소 행렬과 치환 행렬에만 관련됨을 보여준다. 재킷 행렬을 통한 DFT 행렬의 분해는 블록 변조 특성을 나타내는 강한 기하 구조를 갖는다. 이는 재킷 행렬을 통해 분해된 DFT 행렬은 블록 변조 과정으로 해석할 수 있음을 의미한다.

• 한국통신학회논문지
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• 제27권2A호
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• pp.116-123
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• 2002

자켓 행렬(Jacket matrix)은 왈쉬 하다마드(Walsh Hadamard) 행렬 구조를 바탕으로 확장한 행렬이다. 왈쉬 하다마드 행렬이 +1, -1을 기본 원소로 하고 있는 반면 자켓 행렬은 $\pm$1과 $\pm$$\omega$($\pm$j, $\pm$$_2$$^{n}$ )를 각각 원소로 가질 수 있다. 이 행렬은 중앙 부근에 무게(weight)를 갖는데, 하다마드 행렬 크기의 1/4 크기로 부호 부분과 무게 부분으로 구성된다. 본 논문에서는 기존에 행렬 중앙에 강제적으로 무게를 할당하여 자켓 행렬을 구성하였으나, 어떠한 크기의 행렬도 크기와 무게만 정해주면 생성해낼 수 있는 이진 인덱스를 이용한 간단한 비트열 형태의 일반식이 제시된다. 무게는 행과 열의 이진 인덱스의 최상위 두 비트를 Exclusive-OR 연산한 결과가 1인 원소에 부여된다. 또한 분산연산(Distributed Arithmetic:DA) 알고리즘을 이용한 고속자켓변환(Fast Jacket Transform)의 VLSI 구조를 제시한다. 자켓 행렬은 cyclic한 특성을 가지고 있어서 암호화, 정보 이론 및 WCDMA의 복소수 확산 QPSK 변조부에 응용될 수 있다.

• Journal of Communications and Networks
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• 제17권6호
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• pp.634-646
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• 2015

Assuming perfect channel state information (CSI) at the transmitter and receiver, the optimization problem of maximizing the minimum Euclidean distance between two received signals by a linear precoder is considered for multiple-input multiple-output (MIMO) systems with arbitrary dimensions and arbitraryary quadrature amplitude modulation (QAM) input. A general precoding framework is first presented based on the Gram matrix, which is shown for 2-dimensional (2-D) and 3-dimensional (3-D) MIMO systems when employing the ellipse expanding method (EEM). An extended precoder for high-dimensional MIMO system is proposed following the precoding framework, where the Gram matrix for high-dimensional precoding matrix can be generated through those chosen from 2-D and 3-D results in association with a permutation matrix. A complexity-reduced maximum likelihood detector is also obtained according to the special structure of the proposed precoder. The analytical and numerical results indicate that the proposed precoder outperforms the other precoding schemes in terms of both minimum distance and bit error rate (BER).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2657-2675
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• 2013

A novel neighbor selection-based fingerprinting algorithm using matrix correlation (MC) for Wi-Fi localization is presented in this paper. Compared with classic fingerprinting algorithms that usually employ a single received signal strength (RSS) sample, the presented algorithm uses multiple on-line RSS samples in the form of a matrix and measures correlations between the on-line RSS matrix and RSS matrices in the radio-map. The algorithm makes efficient use of on-line RSS information and considers RSS variations of reference points (RPs) for localization, so it offers more accurate localization results than classic neighbor selection-based algorithms. Based on the MC algorithm, an error estimation method using artificial neural network is also presented to fuse available information that includes RSS samples and localization results computed by the MC algorithm and model the nonlinear relationship between the available information and localization errors. In the on-line phase, localization errors are estimated and then used to correct the localization results to reduce negative influences caused by a static radio-map and RP distribution. Experimental results demonstrate that the MC algorithm outperforms the other neighbor selection-based algorithms and the error estimation method can reduce the mean of localization errors by nearly half.

• BMB Reports
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• 제53권7호
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• pp.349-356
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• 2020

Mass spectrometry (MS) is an ideal tool for analyzing multiple types of (bio)molecular information simultaneously in complex biological systems. In addition, MS provides structural information on targets, and can easily discriminate between true analytes and background. Therefore, imaging mass spectrometry (IMS) enables not only visualization of tissues to give positional information on targets but also allows for molecular analysis of targets by affording the molecular weights. Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) MS is particularly effective and is generally used for IMS. However, the requirement for an organic matrix raises several limitations that get in the way of accurate and reliable images and hampers imaging of small molecules such as drugs and their metabolites. To overcome these problems, various organic matrix-free LDI IMS systems have been developed, mostly utilizing nanostructured surfaces and inorganic nanoparticles as an alternative to the organic matrix. This minireview highlights and focuses on the progress in organic matrix-free LDI IMS and briefly discusses the use of other IMS techniques such as desorption electrospray ionization, laser ablation electrospray ionization, and secondary ion mass spectrometry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.3057-3075
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• 2020

End-to-end network delay plays an vital role in distributed services. This delay is used to measure QoS (Quality-of-Service). It would be beneficial to know all node-pair delay information, but unfortunately it is not feasible in practice because the use of active probing will cause a quadratic growth in overhead. Alternatively, using the measured network delay to estimate the unknown network delay is an economical method. In this paper, we adopt the state-of-the-art matrix completion technology to better estimate the network delay from limited measurements. Although the number of measurements required for an exact matrix completion is theoretically bounded, it is practically less helpful. Therefore, we propose an online adaptive sampling algorithm to measure network delay in which statistical leverage scores are used to select potential matrix elements. The basic principle behind is to sample the elements with larger leverage scores to keep the traits of important rows or columns in the matrix. The amount of samples is adaptively decided by a proposed stopping condition. Simulation results based on real delay matrix show that compared with the traditional sampling algorithm, our proposed sampling algorithm can provide better performance (smaller estimation error and less convergence pressure) at a lower cost (fewer samples and shorter processing time).

• 대한전자공학회논문지SP
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• 제45권5호
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• pp.52-62
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• 2008

본 논문에서는 임의의 블록 변환 영역에서 영상의 특성에 적절한 필터를 사용하여 영상의 해상도를 변환하는 기법을 개발 한다. 이를 위하여 임의의 직교 transform 영역에서 해상도 변환을 수행하는 모든 과정을 matrix 곱으로 표현하여 해상도 변환을 수행하는 matrix를 유도한다. 해상도 변환을 수행하는 matrix는 영상 특성에 알맞은 필터를 선택하여 사용할 수 있도록 설계한다. 개발된 기법은 다양한 transform 영역에 적용할 수 있고, 동영상 부호화시 발생되는 inter/intra block들이 혼합되어 있는 영상의 해상도 변환에 적용 가능함을 실험을 통하여 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.5860-5876
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• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1307-1312
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• 2009

Design is an act based on multidisciplinary information. The involvement of various stakeholders makes it difficult to process, plan, and integrate. Iteration is frequent in most of the engineering design and development projects including construction. Design iterations cause rework, and extra efforts are required to get the optimal sequence and to manage the projects. The simple project management techniques are insufficient to fulfill the requirements of integrated design. This paper entails two things: design structure matrix and design parameters' information based model. The emphasis has been given to optimal sequence and crucial iteration using design structure matrix analysis technique. The design projects have been studied using survey data from industry. The optimal sequence and crucial iterations results have been utilized for proposed model. Model integrates two things: information about produced- required key design parameters and information of design changes during the design process. It will help to get familiar with Design management in order to fulfill contemporary needs.

• ETRI Journal
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• 제24권6호
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• pp.469-472
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• 2002

Speaker adaptation techniques are generally used to reduce speaker differences in speech recognition. In this work, we focus on the features fitted to a linear regression-based speaker adaptation. These are obtained by feature transformation based on independent component analysis (ICA), and the feature transformation matrices are estimated from the training data and adaptation data. Since the adaptation data is not sufficient to reliably estimate the ICA-based feature transformation matrix, it is necessary to adjust the ICA-based feature transformation matrix estimated from a new speaker utterance. To cope with this problem, we propose a smoothing method through a linear interpolation between the speaker-independent (SI) feature transformation matrix and the speaker-dependent (SD) feature transformation matrix. From our experiments, we observed that the proposed method is more effective in the mismatched case. In the mismatched case, the adaptation performance is improved because the smoothed feature transformation matrix makes speaker adaptation using noisy speech more robust.