• Title/Summary/Keyword: matrix representation

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Dynamic Incidence Matrix Representation of Timed Petri Nets and Its Applications for Performance Analysis

  • Shon, J.G.;Hwang, C.S.;Baik, D.K.
    • Journal of the Korean Operations Research and Management Science Society
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    • v.16 no.2
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    • pp.128-147
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    • 1991
  • We propose a dynamic incidence matrix (DIM) for reflecting states and time conditions of a timed Petri net (TPN) explicitly. Since a DIM consists of a conventional incidence matrix, two time-related vectors and two state-related vectors, we can get the advantages inherent in the conventional incidence matrix of describing a static structure of a system as well as another advantage of expressing time dependent state transitions. We introduce an algorithm providing the DIM with a state transition mechanism. Because the algorithm is, in fact, an algorithmic model for discrete event simulation of TPN models, we provide a theoretical basis of model transformation of a TPN model into a DEVS(Discrete Event system Specification) model. By executing the algorithm we can carry out performance analysis of computer communication protocols which are represented TPN models.

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Representation of Wavelet Transform using a Matrix Form and Its Implementation

  • Kurosaki, Masayuki;Nishikawa, Kiyoshi;Kiya, Hitoshi
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.282-285
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    • 2000
  • Three representations are known to implement the discrete wavelet transform (DWT) ; i.e., direct, lifting and matrix forms. In these representations, direct and lifting forms are well known so far. This paper derives the matrix form of the DWT from the direct form. Then, we implement these three representations on a programmable digital signal processor (in the following, DSP processor) and compare them in terms of the number of calculations and instruction cycles. As a result, we confirm that the lifting form has the lowest number of calculations and cycles, and the matrix form has an effective decrease in the number of cycles than other representations on the DSP processor.

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Optimal Grayscale Morphological Filters Under the LMS Criterion (LMS 알고리즘을 이용한 형태학 필터의 최적화 방안에 관한 연구)

  • 이경훈;고성제
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.6
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    • pp.1095-1106
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    • 1994
  • This paper presents a method for determining optimal grayscale function processing(FP) morphological filters under the least square (LMS) error criterion. The optimal erosion and dilation filters with a grayscale structuring element(GSE) are determined by minimizing the mean square error (MSE) between the desired signal and the filter output. It is shown that convergence of the erosion and dilation filters can be achieved by a proper choice of the step size parameter of the LMS algorithm. In an attempt to determine optimal closing and opening filters, a matrix representation of both opening and closing with a basis matrix is proposed. With this representation, opening and closing are accomplished by a local matrix operation rather than cascade operations. The LMS and back-propagation algorithm are utilzed for obtaining the optimal basis matrix for closing and opening. Some results of optimal morphological filters applied to 2-D images are presented.

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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.

Vehicle Recognition using Non-negative Tensor Factorization (비음수 텐서 분해를 이용한 차량 인식)

  • Ban, Jae Min;Kang, Hyunchul
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.5
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    • pp.136-146
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    • 2015
  • The active control of a vehicle based on vehicle recognition is one of key technologies for the intelligent vehicle, and the part-based image representation is necessary to recognize vehicles with only partial shapes of vehicles especially in urban scene where occlusions frequently occur. In this paper, we implemented a part-based image representation scheme using non-negative tensor factorization(NTF) and realized a robust vehicle recognition system using the NTF feature. The result shows that the proposed method gives more intuitive part-based representation and more robust recognition in urban scene.

Adjustment Program for Large Sparse Geodetic Networks (희박행렬의 기법을 이용한 대규모 측지망의 조정)

  • Lee, Young Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.11 no.4
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    • pp.143-150
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    • 1991
  • This paper presents an overview of a system of computer programs for the solution of a large geodetic network of about 2,000 stations. The system arranges the matrices in systematic sparse form which is applied to observation equations of RR(C)U (Row-wise Representation Complete Unordered) type and to normal equations of RR(U)U (Row-wise Representation Upper Unordered) type. The solution is done by a Modified Cholesky's algorithm in view of large networks. The implementation program are tested in PC-386 by korean new secondary networks, the results show that the sparse techniques are highly useful to geodetic networks in core-storage management and processing time.

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Drift Handling in Object Tracking by Sparse Representations (희소성 표현 기반 객체 추적에서의 표류 처리)

  • Yeo, JungYeon;Lee, Guee Sang
    • Smart Media Journal
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    • v.5 no.1
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    • pp.88-94
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    • 2016
  • In this paper, we proposed a new object tracking algorithm based on sparse representation to handle the drifting problem. In APG-L1(accelerated proximal gradient) tracking, the sparse representation is applied to model the appearance of object using linear combination of target templates and trivial templates with proper coefficients. Also, the particle filter based on affine transformation matrix is applied to find the location of object and APG method is used to minimize the l1-norm of sparse representation. In this paper, we make use of the trivial template coefficients actively to block the drifting problem. We experiment the various videos with diverse challenges and the result shows better performance than others.

An Analysis of Arbitrarily Shaped Microstrip Antennas Using Transmission - Line Matrix Representation and Moment Methods (전송선로의 매트릭스 표현법과 모멘트법을 이용한 임의 형태를 갖는 마이크로스트립 안테나의 해석)

  • 조원서;김정기
    • The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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    • v.2 no.2
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    • pp.11-18
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    • 1991
  • In this paper, the analysis of arbitrarily shaped microstrip antennas is described. The analysis method is based on the transmission - line matrix representation for the interior problem and the moment method for the problem along the peripheries of the patch. Using this method, the input impedance and other antenna parameters are calculated and compared with experimental results for a circular and an equilateral triangular microstrip antenna. For all of the results, theoretical and expreimental results are in good agreement and the validity of the method is confirmed. This analysis can also be used to analyze microstrip antennas with shorting pins.

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A Sequential Orientation Kalman Filter for AHRS Limiting Effects of Magnetic Disturbance to Heading Estimation

  • Lee, Jung Keun;Choi, Mi Jin
    • Journal of Electrical Engineering and Technology
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    • v.12 no.4
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    • pp.1675-1682
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    • 2017
  • This paper deals with three dimensional orientation estimation algorithm for an attitude and heading reference system (AHRS) based on nine-axis inertial/magnetic sensor signals. In terms of the orientation estimation based on the use of a Kalman filter (KF), the quaternion is arguably the most popular orientation representation. However, one critical drawback in the quaternion representation is that undesirable magnetic disturbances affect not only yaw estimation but also roll and pitch estimations. In this paper, a sequential direction cosine matrix-based orientation KF for AHRS has been presented. The proposed algorithm uses two linear KFs, consisting of an attitude KF followed by a heading KF. In the latter, the direction of the local magnetic field vector is projected onto the heading axis of the inertial frame by considering the dip angle, which can be determined after the attitude KF. Owing to the sequential KF structure, the effects of even extreme magnetic disturbances are limited to the roll and pitch estimations, without any additional decoupling process. This overcomes an inherent issue in quaternion-based estimation algorithms. Validation test results show that the proposed method outperforms other comparison methods in terms of the yaw estimation accuracy during perturbations and in terms of the recovery speed.

Vehicle Recognition using NMF in Urban Scene (도심 영상에서의 비음수행렬분해를 이용한 차량 인식)

  • Ban, Jae-Min;Lee, Byeong-Rae;Kang, Hyun-Chul
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.7C
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    • pp.554-564
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    • 2012
  • The vehicle recognition consists of two steps; the vehicle region detection step and the vehicle identification step based on the feature extracted from the detected region. Features using linear transformations have the effect of dimension reduction as well as represent statistical characteristics, and show the robustness in translation and rotation of objects. Among the linear transformations, the NMF(Non-negative Matrix Factorization) is one of part-based representation. Therefore, we can extract NMF features with sparsity and improve the vehicle recognition rate by the representation of local features of a car as a basis vector. In this paper, we propose a feature extraction using NMF suitable for the vehicle recognition, and verify the recognition rate with it. Also, we compared the vehicle recognition rate for the occluded area using the SNMF(sparse NMF) which has basis vectors with constraint and LVQ2 neural network. We showed that the feature through the proposed NMF is robust in the urban scene where occlusions are frequently occur.