• Journal of the Korean Mathematical Society
• /
• v.58 no.4
• /
• pp.921-948
• /
• 2021

We continue the investigations in [6] extending the Bruhat order on n × n alternating sign matrices to our more general setting. We show that the resulting partially ordered set is a graded lattice with a well-define rank function. Many illustrative examples are given.

• Honam Mathematical Journal
• /
• v.42 no.2
• /
• pp.269-291
• /
• 2020

In this paper, we get acquainted to a new generalization of the modified Hermite matrix polynomials. An explicit representation and expansion of the Matrix exponential in a series of these matrix polynomials is obtained. Some important properties of Modified Hermite Matrix polynomials such as generating functions, recurrence relations which allow us a mathematical operations. Also we drive expansion formulae and some operational representations.

• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2002.05a
• /
• pp.203-206
• /
• 2002

The present study proposes a theoretical model for predicting the matrix crack density growth of each layer in composite laminates subjected to thermo-mechanical loads. Each layer with matrix cracks is treated as an equivalent continuum of degraded elastic stiffnesses which are functions of the matrix crack density in each slyer. The energy release rate as a function of the degraded elastic stiffnesses is then calculated for each layer as functions of thermo-mechanical loads externally applied to the laminate. The matrix crack densities of each layer in general laminates are predicted as functions of the thermo-mechanical loads applied to a number of laminates. Comparisons of the present study with experimental data in the open literatures are also provided.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.5
• /
• pp.1138-1145
• /
• 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 Institute of Telematics and Electronics A
• /
• v.32A no.10
• /
• pp.73-80
• /
• 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
• /
• 1999.06a
• /
• pp.745-748
• /
• 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.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.2
• /
• pp.288-296
• /
• 1997

Curved beam elements with two nodes based on shallow beam geometry and strain interpolations are employed in eigenvalue analysis. In these elements, the displacement interpolation functions and mass matrices are consistent with strain fields. To assess the quality of the element mass matrix in free vibration problems, several numerical experiments are performed. In these analysis, both the inconsistent mass matrices using linear displacement interpolation function and the consistent mass matrices are used to show the difference. The numerical results demonstrate that the accuracy is closely related to the property of the mass matrix as well as that of the stiffness matrix and that the mass matrix consistent with strain fields is very beneficial to eigenvalue analysis. Also, it is proved that the strain based elements are very efficient in a wide range of element aspect ratios and curvature properties.

• ETRI Journal
• /
• v.39 no.6
• /
• pp.841-850
• /
• 2017

We investigate neural network image reconstruction for magnetic particle imaging. The network performance strongly depends on the convolution effects of the spectrum input data. The larger convolution effect appearing at a relatively smaller nanoparticle size obstructs the network training. The trained single-layer network reveals the weighting matrix consisting of a basis vector in the form of Chebyshev polynomials of the second kind. The weighting matrix corresponds to an inverse system matrix, where an incoherency of basis vectors due to low convolution effects, as well as a nonlinear activation function, plays a key role in retrieving the matrix elements. Test images are well reconstructed through trained networks having an inverse kernel matrix. We also confirm that a multi-layer network with one hidden layer improves the performance. Based on the results, a neural network architecture overcoming the low incoherence of the inverse kernel through the classification property is expected to become a better tool for image reconstruction.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.10
• /
• pp.2171-2179
• /
• 2009

In this paper, we propose a novel Image Encryption using MLCA (Maximum Length Cellular Automata) and CAT (Cellular Automata Transform). Firstly, we use the Wolfram rule matrix to generate MLCA state transition matrix T. Then the state transition matrix T changes pixel value of original image according to pixel position. Next, we obtain Gateway Values to generate 2D CAT basis function. Lastly, the basis function encrypts the MLCA encrypted image into cellular automata space. The experimental results and security analysis show that the proposed method guarantees better security and non-lossy encryption.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.5 no.4
• /
• pp.152-159
• /
• 1997

This paper presents a vibration analysis method of crank shaft of six cylinder internal combustion engine. For simple analysis journal, pin and arm parts were assumed to have uniform section. Transfer Matrix Method was used, considering branched part and coordinate transformation part. Natural frequencies, modeshapes and transfer functions of crank shaft were investigated based upon the Euler beam theory: It was shown that the calculated natural frequencies, modeshapes agree well with the existing paper results.