• Title/Summary/Keyword: Matrix Vector

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Performance Improvement of Sensorless Vector Control for Induction Motor Drives Driven By Matrix Converter Using Non-Linearity Compensation and Disturbance Observer (비선형 모델링과 외란 관측기를 이용한 Matrix Converter로 구동되는 유도전동기 센서리스 벡터제어의 성능 개선)

  • Kyo-Beum Lee
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.53 no.8
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    • pp.500-508
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    • 2004
  • This paper presents a new sensorless vector control system for high performance induction motor drives fed by a matrix converter with non-linearity compensation and disturbance observer. The nonlinear voltage distortion that is caused by commutation delay and on-state voltage drop in switching device is corrected by a new matrix converter modeling. The lumped disturbances such as parameter variation and load disturbance of the system are estimated by the radial basis function network (RBFN). An adaptive observer is also employed to bring better responses at the low speed operation. Experimental results are shown to illustrate the performance of the proposed system.

Joint Time Delay and Angle Estimation Using the Matrix Pencil Method Based on Information Reconstruction Vector

  • Li, Haiwen;Ren, Xiukun;Bai, Ting;Zhang, Long
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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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.

COMPLETION FOR TIGHT SIGN-CENTRAL MATRICES

  • Cho, Myung-Sook;Hwang, Suk-Geun
    • Bulletin of the Korean Mathematical Society
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    • v.43 no.2
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    • pp.343-352
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    • 2006
  • A real matrix A is called a sign-central matrix if for, every matrix $\tilde{A}$ with the same sign pattern as A, the convex hull of columns of $\tilde{A}$ contains the zero vector. A sign-central matrix A is called a tight sign-central matrix if the Hadamard (entrywise) product of any two columns of A contains a negative component. A real vector x = $(x_1,{\ldots},x_n)^T$ is called stable if $\|x_1\|{\leq}\|x_2\|{\leq}{\cdots}{\leq}\|x_n\|$. A tight sign-central matrix is called a $tight^*$ sign-central matrix if each of its columns is stable. In this paper, for a matrix B, we characterize those matrices C such that [B, C] is tight ($tight^*$) sign-central. We also construct the matrix C with smallest number of columns among all matrices C such that [B, C] is $tight^*$ sign-central.

Fast Multi-Rate LDPC Encoder Architecture for WiBro System (WiBro 시스템을 위한 고속 LDPC 인코더 설계)

  • Kim, Jeong-Ki;S.P., Balakannan;Lee, Moon-Ho
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.45 no.7
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    • pp.1-8
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    • 2008
  • Low Density Parity Check codes(LDPC) are recently focused on communication systems due to its good performance. The standard of WiBro has also included LDPC codes as a channel coding. The weak point of implementation for LDPC encoder is that conventional binary Matrix Vector Multiplier has many clock cycles which limit throughput. In this paper, we propose semi-parallel architecture by using cyclic shift registers and exclusive-OR without conventional Matrix Vector Multipliers over the standard parity check matrices with Circulant Permutation Matrices(CPM). Furthermore, multi-rate encoder is designed by using proposed architecture. Our encoder with multi-rate for IEEE 802.16e LDPC has lower clock cycles and higher throughput.

A Classifier for Textured Images Based on Matrix Feature (행렬 속성을 이용하는 질감 영상 분별기)

  • 김준철;이준환
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.3
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    • pp.91-102
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    • 1994
  • For the analysis of textured image, it requires large storage space and computation time to calculate the matrix features such as SGLDM(Spatial Gray Level Dependence Matrix). NGLDM(Neighboring Gray Level Dependence Matrix). NSGLDM(Neighboring Spatial Gray Level Dependence Matrix) and GLRLM(Gray Level Run Length Matrix). In spite of a large amount of information that each matrix contains, a set of several correlated scalar features calculated from the matrix is not sufficient to approximate it. In this paper, we propose a new classifier for textured images based on these matrices in which the projected vectors of each matrix on the meaningful directions are used as features. In the proposed method, an unknown image is classified to the class of a known image that gives the maximum similarity between the projected model vector from the known image and the vector from the unknown image. In the experiment to classify images of agricultural products, the proposed method shows good performance as much as 85-95% of correct classification ratio.

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A Parallel-Architecture Processor Design for the Fast Multiplication of Homogeneous Transformation Matrices (Homogeneous Transformation Matrix의 곱셈을 위한 병렬구조 프로세서의 설계)

  • Kwon Do-All;Chung Tae-Sang
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.12
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    • pp.723-731
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    • 2005
  • The $4{\times}4$ homogeneous transformation matrix is a compact representation of orientation and position of an object in robotics and computer graphics. A coordinate transformation is accomplished through the successive multiplications of homogeneous matrices, each of which represents the orientation and position of each corresponding link. Thus, for real time control applications in robotics or animation in computer graphics, the fast multiplication of homogeneous matrices is quite demanding. In this paper, a parallel-architecture vector processor is designed for this purpose. The processor has several key features. For the accuracy of computation for real application, the operands of the processors are floating point numbers based on the IEEE Standard 754. For the parallelism and reduction of hardware redundancy, the processor takes column vectors of homogeneous matrices as multiplication unit. To further improve the throughput, the processor structure and its control is based on a pipe-lined structure. Since the designed processor can be used as a special purpose coprocessor in robotics and computer graphics, additionally to special matrix/matrix or matrix/vector multiplication, several other useful instructions for various transformation algorithms are included for wide application of the new design. The suggested instruction set will serve as standard in future processor design for Robotics and Computer Graphics. The design is verified using FPGA implementation. Also a comparative performance improvement of the proposed design is studied compared to a uni-processor approach for possibilities of its real time application.

Performance Improvement of Reduced Order Extended Luenberger Observer(ROELO) based Sensorless Vector Control Fed by Matrix Converter With Non-linearity Modeling (비선형모델을 이용한 matrix convertor로 구동되는 축소차원 확장 루엔버거 관측기기반의 유도전동기 센서리스 벡터제어의 성능개선)

  • Lee Kyo-Beum
    • The Transactions of the Korean Institute of Power Electronics
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    • v.10 no.4
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    • pp.363-372
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    • 2005
  • This paper presents an improved sensorless vector control system for high performance induction motor drives fed by a matrix converter with non-linearity compensation. The nonlinear voltage distortion that is caused by commutation delay and on-state voltage drop in switching devices is corrected by a new matrix converter model. A Reduced Order Extended Luenberger Observer (ROELO) is employed to bring better response in the whole speed operation range and a method to select the observer gain is presented. Experimental results are shown to illustrate the performance of the proposed system.

A Study of General AC Machine Modeling with Matrix Vector Using DQ Transformation

  • Hong, Sun-Ki
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.27 no.8
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    • pp.98-104
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    • 2013
  • AC machines are in wide use in industry and d-q transformation from 3 phase of a, b, c is commonly used to analyze these kinds of machines. The equivalent circuits of d and q axis are, however, generally cross coupled and difficult to analyze. In this study, a modeling technique of AC machine including induction and PM synchronous motors using matrix vector is proposed. With that model, it can not only explain the AC machines physically but also make it simple to analyze them. The separating process of d and q components is not needed in this model and this model can be applied to analyze asymmetric motors like IPMSM machine. With this technique, the model becomes simple, easy to understand physically, and yields results that are the same as those from other models. These simulation results of the proposed model for induction motor are compared with those of other models to verify the method proposed.

One-Class Support Vector Learning and Linear Matrix Inequalities

  • Park, Jooyoung;Kim, Jinsung;Lee, Hansung;Park, Daihee
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.1
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    • pp.100-104
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    • 2003
  • The SVDD(support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the kernel feature space in order to distinguish a set of normal data from all other possible abnormal objects. The major concern of this paper is to consider the problem of modifying the SVDD into the direction of utilizing ellipsoids instead of balls in order to enable better classification performance. After a brief review about the original SVDD method, this paper establishes a new method utilizing ellipsoids in feature space, and presents a solution in the form of SDP(semi-definite programming) which is an optimization problem based on linear matrix inequalities.

Construction of Expression Vector for the Production of Transgenic Animal using Matrix Attachment Region

  • 김순정;이연근;이풍연;이현기;정희경;서명규;박진기;장원경
    • Proceedings of the KSAR Conference
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    • 2003.06a
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    • pp.40-40
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    • 2003
  • 형질전환체 제작 시 발현벡터가 삽입되는 위치에 따라 발현 또는 억제되는 현상인 ‘position effect(위치효과)’를 극복하기 위해 Matrix Attachment Region(MAR)을 포함하는 발현벡터를 제작하였다 MAR는 핵 기질(nuclear matrix) 부착 부위로 발현조절에 관여하는 전사인자 등이 존재하는 핵 기질 부착부위로, 삽입된 발현벡터가 전사활성을 할 수 있는 게놈 환경을 제공해 주어 형질전환 유전자 발현을 향상시켜 준다고 보고되고 있다. 본 연구에서는 사람에서 이미 분리되어 염기서열이 밝혀진 MAR를 PCR로 증폭하였다. 증폭된 1,270 bp의 human alpha-1-antitrypsin MAR와 1,080 bp human corticosteroid binding globulin promoter MAR를 T vector에 클로닝하여 염기서열을 확인했으며 발현벡터 클로닝에 사용하였다. 유용 유전자와 세포 형질전환에 사용할 선별 유전자로 neo를 포함하며, 그 외 벡터골격은 pGL3 control vector를 사용하여 기본 발현벡터를 제작하였다. 이 벡터에 MAR를 5', 3' 양쪽 또는 한쪽만 포함하도록 클로닝하였다. 이는 MAR의 위치에 따른 게놈내 삽입 및 발현효과를 확인하여 형질전환동물 생산용 발현벡터로 활용하고자 한다.

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