• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.1861-1871
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• 1994

This paper presents efficient real time software implementation methods for the grayscale morphological composite function processing (FP) system. The proposed method is based on a matrix representation of the composite FP system using a basis matrix composed of structuring elements. We propose a procedure to derive the basis matrix for composite FP systems with any grayscale structuring element (GSE). It is shown that composite FP operations including morphological opening and closing are more efficiently accomplished by a local matrix operation with the basis matrix rather than cascade operations, eliminating delays and requiring less memory storage. In the second part of this paper, a VLSI implementation architecture for grayscale morphological operators is presented. The proposed implementation architecture employs a bit-serial approach which allows grayscale morphological operations to be decomposed into bit-level binary operation unit for the p-bit grayscale singnal. It is shown that this realization is simple and modular structure and thus is suitable for VLSI implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3913-3934
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• 2021

Real-time prediction of Web service of quality (QoS) provides more convenience for web services in cloud environment, but real-time QoS prediction faces severe challenges, especially under the cold-start situation. Existing literatures of real-time QoS predicting ignore that the QoS of a user/service is related to the QoS of other users/services. For example, users/services belonging to the same group of category will have similar QoS values. All of the methods ignore the group relationship because of the complexity of the model. Based on this, we propose a real-time Matrix Factorization based Clustering model (MFC), which uses category information as a new regularization term of the loss function. Specifically, in order to meet the real-time characteristic of the real-time prediction model, and to minimize the complexity of the model, we first map the QoS values of a large number of users/services to a lower-dimensional space by the PCA method, and then use the K-means algorithm calculates user/service category information, and use the average result to obtain a stable final clustering result. Extensive experiments on real-word datasets demonstrate that MFC outperforms other state-of-the-art prediction algorithms.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2705-2708
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• 2003

In this paper, we propose a method that applies matrix decomposition technique to the connection of actuator capabilities of each robot to object acceleration limits for multiple cooperative robot systems. The robot systems under consideration are composed of several robot manipulators and each robot contacts a single object to carry the object while satisfying the constraints described in kinematics as well as dynamics. By manipulating kinematic and dynamic equations of both robots and objects, we at first derive a matrix relating joint torques with object acceleration, manipulate the null space of the matrix, and then we decompose the matrix into three parts representing indeterminancy, connectivity, and redundancy. With the decomposed matrix we derive the boundaries of object accelerations from given joint actuators. To show the validity of the proposed method some examples are given in which the results can be expected by intuitive observation.

• Communications of the Korean Mathematical Society
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• v.11 no.4
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• pp.1159-1174
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• 1996

The spectrum of the Laplacian matrix of a graph gives an information of the structure of the graph. For example, the product of non-zero eigenvalues of the characteristic polynomial of the Laplacian matrix of a graph with n vertices is n times of the number of spanning trees of that graph. The characteristic polynomial of the Laplacian matrix of a graph tells us the number of spanning trees and the connectivity of given graph. in this paper, we compute the characteristic polynomial of the Laplacian matrix of a graph bundle when its voltage lie in an abelian subgroup of the full automorphism group of the fibre; in particular, the automorphism group of the fibre is abelian. Also we study a relation between the characteristic polynomial of the Laplacian matrix of a graph G and that of the Laplacian matrix of a graph bundle over G. Some applications are also discussed.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1138-1145
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• 2013

A novel predictive current control strategy for a sparse matrix converter is presented. The sparse matrix converter is functionally-equivalent to the direct matrix converter but has a reduced number of switches. The predictive current control uses a model of the system to predict the future value of the load current and generates the reference voltage vector that minimizes a given cost function so that space vector modulation is achieved. The results show that the proposed controller for sparse matrix converters controls the load current very effectively and performs very well through simulation and experimental results.

• Journal of the Korean Mathematical Society
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• v.51 no.5
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• pp.897-918
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• 2014

This paper addresses multi-window Gabor frames with rational time-frequency product. Such issue was considered by Zibulski and Zeevi (Appl. Comput. Harmonic Anal. 4 (1997), 188-221) in terms of Zak transform matrix (so-called Zibuski-Zeevi matrix), and by many others. In this paper, we introduce of a new Zak transform matrix. It is different from Zibulski-Zeevi matrix, but more direct and convenient for our purpose. Using such Zak transform matrix we characterize rational time-frequency multi-window Gabor frames (Riesz bases and orthonormal bases), and Gabor duals for a Gabor frame. Some examples are also provided, which show that our Zak transform matrix method is efficient.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.10
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• pp.73-80
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• 1995

In this paper, a synthesis tool using matrix operations for designing multi-level Reed Muller circuits is described which has been named as MRM (Multi-level Reed Muller Minimizer). The synthesis method which uses matrix operations has advantages in effectively minimizing chip area, delay optimization and fault detection capability. However, it uses only truth-table type maps for inputs, synthesizing only small circuits. To overcome the weakness, our method accepts two-level description of a logic function. Since the number of cubes in the two-level description is small, the input matrix becomes small and large circuits can be synthesized. To convert two-level representations into multi-level ones, different input patterns are extracted to make a map which can be fed to the matrix operation procedure. Experimental results show better performance than previous methods. The matrix operation method presented in this paper is new to the society of Reed Muller circuits synthesis and provides solid mathematical foundations.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.257-260
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• 2002

This paper describes the pixel of AMOLED(act ive matrix organic light emitting diode) driving circuit by poly-sl technology. The area per pixel is 278um$\times$278um in 120$\times$160(2.2 inch) Driving the OLEDS with active matrix leads to the lower voltage operation, the lower peak pixel currents and the display with much greater efficiency and brightness The role of the active matrix is to provide a constant current throughout the entire frame time and is eliminating the high currents encountered In the passive matrix approach, This design can support the high resolutions expected by the consumer because the current variation specification is norestricted. The pixel has been designed driving TFT threshold voltage cancellation circuit and wide aperture ratio circuit that communizes 4 pixel. The test simulation results and layout are 11% per threshold-current var Eat ion and 12.5% the aperture ratio of increase.

• ETRI Journal
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• v.42 no.3
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• pp.333-340
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• 2020

We consider a hybrid combiner design for downlink massive multiple-input multiple-output systems when there is residual inter-user interference and each user is equipped with a limited number of radio frequency (RF) chains (less than the number of receive antennas). We propose a hybrid combiner that minimizes the mean-squared error (MSE) between the information symbols and the ones estimated with a constant amplitude constraint on the RF combiner. In the proposed scheme, an iterative alternating optimization method is utilized. At each iteration, one of the analog RF and digital baseband combining matrices is updated to minimize the MSE by fixing the other matrix without considering the constant amplitude constraint. Then, the other matrix is updated by changing the roles of the two matrices. Each element in the RF combining matrix is obtained from the phase component of the solution matrix of the optimization problem for the RF combining matrix. Simulation results show that the proposed scheme performs better than conventional matrix-decomposition schemes.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.745-748
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• 1999

This paper propose the method to derive RM(Reed-Muller) expansion coefficients for Multiple-Valued function. The general method to obtain RM expansion coefficient for p valued n variable is derivation of single variable transform matrix and expand it n times using Kronecker product. The transform matrix used is p$^{n}$ $\times$ p$^{n}$ matrix. In this case the size of matrix increases depending on the augmentation of variables and the operation is complicated. Thus, to solving the problem, we propose derivation of RM expansion coefficients using p$\times$p transform matrix and Karnaugh-map.