• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.6 no.4
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• pp.20-27
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• 1995

A numerical simulation is carried out on the directivity synthesis of ultrasonic transducers by point source array. Gauss elimination method is practiced by means of a directive method to realize the desired directivity. Desired directivity is chosen to be that of a directivity of line source, a beam width and a direction arbitrary specified. On the numerical result, Gauss elimination method is showed high speed ca- lculative simulation and stability of system more than iterative method(LMS, DFP). Numerical simulations are carried out by PC(CPU:80486 DX2, RAM 16Mbyte).

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.189-196
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• 1994

This paper describes a parallel computing algorithm in Gauss elimination of Jacobian matrix to large-scale power system. The structure of Jacobian matrix becomes different according to ordering method of buses. In sequential computation buses are ordered to minimize the number of fill-in in the triangulation of the Jacobian matrix. The proposed method develops the parallelism in the Gauss elimination by using ND(nested dissection) ordering. In this procedure the level structure of the power system network is transformed to be long and narrow by using end buses which results in balance of computing load among processes and maximization of parallel computation. Each processor uses the sequential computation method to preserve the sqarsity of matrix.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.333-336
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• 2000

We discuss the direct methods (Gauss-Jordan and Gaussian eliminations) to solve linear systems on distributed memory parallel computers. It will be shown that the so-called row-cyclic storage gives rise to the best performance among the standard three (row-cyclic, column-cyclic and cyclic-cyclic) data storages. We also show that Gauss-Jordan elimination, rather than Gaussian elimination, is highly efficient for the direct solution of linear systems in parallel processing, though Gauss-Jordan elimination requires a larger number of arithmetic operations than Gaussian elimination. Numerical experiment is performed on HITACHI SR12201 with the standard libraries MPI and BLAS.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.163-166
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• 1993

This paper describes an parallell computing algorithm in Gauss elimination of Jacobian matrix to large-scale power system. The structure of Jacobian matrix becomes different according to ordering method of buses. In sequential computation buses are ordered to minimize the number of fill-in in the triangulation of the Jacobian matrix. The proposed method using ND(nested dissection) ordering develops the parallelism in the Gauss elimination to have balance of computing load among processes and each processor uses the sequential computation method to preserve the sparsity of matrix.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.384-392
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• 2012

Recently, much research on blind estimation of the interleaver parameters has been performed by using Gauss-Jordan elimination to find the linearity of the block channel code. When using Gauss-Jordan elimination, the input data to be calculated needs to run as long as the square multiple of the number of the interleaver period. Thus, it has a limit in estimating the interleaver parameters with insufficient input data. In this paper, we introduce and analyze an estimation algorithm which can estimate interleaver parameters by using only 15 percent of the input data length required in the above algorithm. The shorter length of input data to be calculated makes it possible to estimate the interleaver parameters even when limited data is received. In addition, a 80 percent reduction in the number of the interleaver period candidates increases the efficiency of analysis. It is also feasible to estimate both the type and size of the interleaver and the type of channel coding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3458-3481
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• 2021

Existing methods for blind identification of linear block codes without a candidate set are mainly built on the Gauss elimination process. However, the fault tolerance will fall short when the intercepted bit error rate (BER) is too high. To address this issue, we apply the reverse algebra approach and propose a novel "two-step-screening" algorithm by solving the linear error equations on the binary Galois field, or GF(2). In the first step, a recursive matrix partition is implemented to solve the system linear error equations where the coefficient matrix is constructed by the full codewords which come from the intercepted noisy bitstream. This process is repeated to derive all those possible parity-checks. In the second step, a check matrix constructed by the intercepted codewords is applied to find the correct parity-checks out of all possible parity-checks solutions. This novel "two-step-screening" algorithm can be used in different codes like Hamming codes, BCH codes, LDPC codes, and quasi-cyclic LDPC codes. The simulation results have shown that it can highly improve the fault tolerance ability compared to the existing Gauss elimination process-based algorithms.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.436-446
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• 2014

The high intensity of research and modeling in fields of mathematics, physics, biology and chemistry requires new computing resources. For the big computational complexity of such tasks computing time is large and costly. The most efficient way to increase efficiency is to adopt parallel principles. Purpose of this paper is to present the issue of parallel computing with emphasis on the analysis of parallel systems, the impact of communication delays on their efficiency and on overall execution time. Paper focuses is on finite algorithms for solving systems of linear equations, namely the matrix manipulation (Gauss elimination method, GEM). Algorithms are designed for architectures with shared memory (open multiprocessing, openMP), distributed-memory (message passing interface, MPI) and for their combination (MPI + openMP). The properties of the algorithms were analytically determined and they were experimentally verified. The conclusions are drawn for theory and practice.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.12
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• pp.127-138
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• 1985

There are several methods which have been presented up to now in solving the simultaneous linear equations by computer. They are Gaussian Elimination Method, Gauss-Jordan Method, Inverse matrix Method and Gauss-Seidel iterative Method. This paper is not only discussed in their mechanisms compared with their algorithms, depicted flow charts, but also calculated the numbers of arithmetic operations and comparisons in order to criticize their availability. Inverse Matrix Method among em is founded out the smallest in the number of arithmetic operation, but is not the shortest operation time. This paper also indicates the many problems in using these methods and propose the new method which is able to applicate to even small or middle size computers.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.1020-1024
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• 1987

Image segmentation based on the curvature of bi-directiona distribution functions of histogram with no mode informations is proposed. The curvature is an oscillating function and can be approximated to a polynomial form with a least square method using the Chebyshev basis. Nonhomogeneous linea equations are solved by Gauss-elimination method. In the proposed algorithm, critical points of the curvature are obtained on each direction to compensate the segmentation parameters, which can be ignored in only one-directional histogram.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.951-958
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• 2017

In an attack context, the adversary wants to retrieve the message from the intercepted noisy bit stream without any prior knowledge of the channel codes used. The process of finding out the code parameters such as code length, dimension, and generator, for this purpose, is called the blind recognition of channel codes or the reconstruction of channel codes. In this paper, we suggest an improved algorithm of the blind recovery of rate k/n convolutional encoders in a noisy environment. The suggested algorithm improves the existing algorithm by Marazin, et. al. by evaluating the threshold value through the estimation of the channel error probability of the BSC. By applying the soft decision method by Shaojing, et. al., we considerably enhance the success rate of the channel reconstruction.