• Journal of the Korea Computer Industry Society
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• v.2 no.3
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• pp.297-308
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• 2001

We propose an algorithm which can reconstruct the 3D information from geographical information. The conventional techniques, the triangular patches and the Random Fractal Midpoint Displacement (RFMD) method, etc., have often been used to reconstruct natural images. While the RFMD method using Gaussian distribution obtains good results for the symmetric images, it is not reliable on asymmetric images immanent in the nature. Our proposed algorithm employs neural networks for the RFMD method to present the asymmetrical images. By using a neural network for reconstructing the 3D images, we can utilize statistical characteristics of irregular data. We show that our algorithm has a better performance than others by the point of view on the similarity evaluation. And, it seems that our method is more efficient for the mountainous topography which is more rough and irregular.

• Journal of the military operations research society of Korea
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• v.36 no.2
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• pp.11-24
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• 2010

Quick precision-strike capability of the artillery will be an important factor in modern and future war and it's represented by NCW and EBO. This study is based on artillery which has time limitation of firing, such as artillery which hides when not firing, and modeling various situations to decide firing order and who to shoot. The main purpose of this study is to suggest a mathematical programming model and a genetic algorithm which satisfies the limitation of firing time. The objective function is to minimize the total firing time to spend. The results of the suggested algorithm quickly gives a best solution for a large scale field artillery targeting problems.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.5
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• pp.7-13
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• 2001

Modular wavelet neural network combining wavelet theory and modular concept based on single layer neural network have been proposed as an alternative to conventional wavelet neural network and kind of modular network. In this paper, an effective method to construct an optimal modular wavelet network is proposed using genetic algorithm. Genetic Algorithm is used to determine dilations and translations of wavelet basis functions of wavelet neural network in each module. We apply the proposed algorithm to approximation problem and evaluate the effectiveness of the proposed system and algorithm.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.363-369
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• 2002

In this paper, it could improved on the arbitrary nonlinear function learning approximation which have the wavelet neural network based on Adaptive Neuro-Fuzzy Inference System(ANFIS) and the multi-resolution Analysis(MRA) of the wavelet transform. ANFIS structure is composed of a bell type fuzzy membership function, and the wavelet neural network structure become composed of the forward algorithm and the backpropagation neural network algorithm. This wavelet composition has a single size, and it is used the backpropagation algorithm for learning of the wavelet neural network based on ANFIS. It is confirmed to be improved the wavelet base number decrease and the convergence speed performances of the wavelet neural network based on ANFIS Model which is using the wavelet translation parameter learning and bell type membership function of ANFIS than the conventional algorithm from 1 dimension and 2 dimension functions.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.4
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• pp.72-77
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• 1984

A placement program in LSI layout is developed and the results of test are discussed in this paper. In order to achieve 100% wiring, this paper introduces, as a virtual routing method, an algorithm which is close to the real routing. This algorithm is reflected to calculate the channel density. An object function is introduced to achieve minimization of total wire length, number of cuts, and maximum channel density simultaneously. The time complexity for the proposed virtual routing algorithm is O(n2). The time required for the algorithm is very short. This algorithm represents the routing state which is close to minimum wire length. So this algorithm is very proper to the application of placement problem. An auto-placement program is developed by the use of this algorithm. The efficiency of the proposed algorithm is shown in the test of the developed program.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.6
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• pp.768-775
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• 1998

The equalizer is the central part of the receiver and its performance significantly affects the overall performance of the system in the mobile communication. A proposed equalizer is composed of the channel estimator, MLSE based on the Viterbi algorithm and GMSK decoder. The approximation of GMSK with QPSK has great impact on the equalizer design, because it allows us to use the existing simple and efficient algorithms for designing optimal QPSK equalizer. In order to estimate efficiently channel, we use a sliding window algorithm based on energy calculation and cross-correlator. And also a tuning scheme is presented in order to improve the equalizer performance. Simulation results indicate that a proposed equalizer meets the GSM standards easily in terms of performance.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.7
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• pp.213-218
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• 2015

Given two strings X and Y (|X|=m, |Y|=n) over an alphabet ${\Sigma}$, the extended edit distance between X and Y can be computed using dynamic programming in O(mn) time and space. Recently, a parallel algorithm that takes O(m+n) time and O(mn) space using m threads to compute the extended edit distance between X and Y was presented. In this paper, we present an improved parallel algorithm using the shared memory on GPU. The experimental results show that our parallel algorithm runs about 19~25 times faster than the previous parallel algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.310-317
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• 2006

In this paper, we propose a new sequential message-passing decoding algorithm of low-density parity-check (LDPC) codes by partitioning check nodes. This new decoding algorithm shows better bit error rate(BER) performance than that of the conventional message-passing decoding algorithm, especially for small number of iterations. Analytical results tell us that as the number of partitioned subsets of check nodes increases, the BER performance becomes better. We also derive the recursive equations for mean values of messages at variable nodes by using density evolution with Gaussian approximation. Simulation results also confirm the analytical results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.2119-2132
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• 1996

This paper proposes four approaches for approximately realizing nonlinear mappling of interval vectors by neural networks. In the proposed approaches, training data for the learning of neural networks are the paris of interval input vectors and interval target output vectors. The first approach is a direct application of the standard BP (Back-Propagation) algorithm with a pre-processed training data. The second approach is an application of the two BP algorithms. The third approach is an extension of the BP algorithm to the case of interval input-output data. The last approach is an extension of the third approach to neural network with interval weights and interval biases. These approaches are compared with one another by computer simulations.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.6
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• pp.31-37
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• 2013

Modern graphic processors, multimedia processors and audio processors mostly use floating-point number. High-level language such as C and Java use both single precision and double precision floating-point number. In this paper, an algorithm which computes the reciprocal of double precision floating-point number using a 32 bit multiplier is proposed. It divides the mantissa of double precision floating-point number to upper part and lower part, and calculates the reciprocal of the upper part with Newton-Raphson algorithm. And it computes the reciprocal of double precision floating-point number with calculated upper part reciprocal as the initial value. Since the number of multiplications performed by the proposed algorithm is dependent on the mantissa of floating-point number, the average number of multiplications per an operation is derived from some reciprocal tables with varying sizes.