• Journal of applied mathematics & informatics
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• v.31 no.5_6
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• pp.785-794
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• 2013

Soon after Lee and O'Sullivan proposed a new interpolation algorithm for algebraic soft-decision decoding of Reed-Solomon codes, there have been some attempts to apply a coordinate transformation technique to the new algorithm, with a remarkable complexity reducing effect. In this paper, a conceptually simple way of applying the transformation technique to the interpolation algorithm is proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4549-4567
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• 2016

To cope with the complex electromagnetic environment of wireless communication systems, anti-jamming decision methods are necessary to keep the reliability of communication. Basing on the rule-reduced genetic algorithm (RRGA), an anti-jamming decision method is proposed in this paper to adapt to the fast channel variations. Firstly, the reduced decision rules are obtained according to the rough set (RS) theory. Secondly, the randomly generated initial population of the genetic algorithm (GA) is screened and the individuals are preserved in accordance with the reduced decision rules. Finally, the initial population after screening is utilized in the genetic algorithm to optimize the communication parameters. In order to remove the dependency on the weights, this paper deploys an anti-jamming decision objective function, which aims at maximizing the normalized transmission rate under the constraints of minimizing the normalized transmitting power with the pre-defined bit error rate (BER). Simulations are carried out to verify the performance of both the traditional genetic algorithm and the adaptive genetic algorithm. Simulation results show that the convergence rates of the two algorithms increase significantly thanks to the initial population determined by the reduced-rules, without losing the accuracy of the decision-making. Meanwhile, the weight-independent objective function makes the algorithm more practical than the traditional methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.208-212
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• 1998

This paper suggests the method to recognize the various defect patterns of cold mill strip using binary decision tree constructed by genetic algorithm automatically. In case of classifying the complex the complex patterns with high similarity like the defect patterns of cold mill strip, the selection of the optimal feature set and the structure of recognizer is important for high recognition rate. In this paper genetic algorithm is used to select a subset of the suitable features at each node in binary decision tree. The feature subset of maximum fitness is chosen and the patterns are classified into two classes by linear decision function. After this process is repeated at each node until all the patterns are classified respectively into individual classes. In this way , binary decision tree classifier is constructed automatically. After construction binary decision tree, the final recognizer is accomplished by the learning process of neural network using a set of standard p tterns at each node. In this paper, binary decision tree classifier is applied to recognition of the defect patterns of cold mill strip and the experimental results are given to show the usefulness of the proposed scheme.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1998.10a
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• pp.421-431
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• 1998

Error control performance of the (16, 7) minimum-bandwidth binary error cotrol line code (MB-ECLC) according to decoding algorithms is analyzed and compared in this paper. As a result , when retransmission is not allowed or meaningless. to reduce performance degradation ad computational burden. the modified soft decision decoding algorithm using the structure of (16,7) MB-ELEC is proposed. The error cotnrol capability of this modified algorithm is far better than that of a hard decision decoding algorithm, and almost same as that of a full soft decision decoding algorithm. In additino, the number of comparisons for the modified algorithm is decreased more than 5 times as compared with a full soft decision decoding algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.267-276
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• 2004

Much of previous attention on researches of the decision tree focuses on the splitting criteria and optimization of tree size. Nowadays the quantity of the data increase and relation of variables becomes very complex. And hence, this comes to have plenty number of unnecessary node and leaf. Consequently the confidence of the explanation and forecasting of the decision tree falls off. In this research report, we propose some decision tree algorithms considering the interaction of predictor variables. A generic algorithm, the k-1 Algorithm, dealing with the interaction with a combination of all predictor variable is presented. And then, the extended version k-k Algorithm which considers with the interaction every k-depth with a combination of some predictor variables. Also, we present an improved algorithm by introducing control parameter to the algorithms. The algorithms are tested by real field credit card data, census data, bank data, etc.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.783-789
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• 2005

This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.297-300
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• 2007

Due to its impressive compression performance, the H.264 video coder is highlighted in the video communications industry, such as DMB (Digital Multimedia Broadcasting), PMP (Portable Multimedia Player), etc. The main bottleneck to use the H.264 coder lays in the computational complexity, i.e. five times more complex than the market leading MPEG-4 Simple Profile codec. In this paper, we propose the hierarchical mode decision method for intraframe coding for the reduction of the computation complexity of the encoder. By determining the mode group early, the propose algorithm can skip the computationally demanding computation in the mode decision. The proposed algorithm is composed of three steps: $16{\times}16$ mode decision, $4{\times}4$ mode-group decisions, and final mode decision among the selected mode group. The simulation results show that the proposed algorithm achieves 20% to 50% reduction in the computational complexity compared with the conventional algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.1
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• pp.93-101
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• 2008

It is difficult for a MWR(Missile Warning Radar) to perform a threat decision accurately since there is no tracking part which gives more accurate threat information to the MWR. In this paper, the threat decision algorithm is proposed using an azimuth angular rate to improve the accuracy. The azimuth angular rate is dependent upon the direction of an approaching target. The target is classified into a threat or non-threat using a boundary condition of the azimuth angular rate. The boundary condition is determined using the Monte-Carlo simulation. The performance of the proposed algorithm is evaluated using this condition at field tests of MWR. The efficiency of the proposed method for the threat decision is proved by comparing the results of field tests with the simulation results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1895-1902
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• 2011

The soft-decision e-BCH decoding algorithm based on the Chase algorithm is adopted in DVB-RCS NG systems. For implementation, it is necessary to decide the number of optimal quantization bits when soft-decision e-BCH decoding algorithm is processed. Also, the performance must be satisfied. Therefore, in this paper, when the soft-decision e-BCH decoder is implemented, we select the number of optimal quantization bits using BER performance.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.2
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• pp.78-85
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• 2002

We introduce a rotational decision-directed joint algorithm of blind equalization coupled with carrier recovery for 32-QAM demodulation with high symbol rate. The proposed carrier recovery, which we call a rotational decision-directed carrier recovery(RDDCR), removes the residual phase difference by rotating the decision boundary for the kth received symbol by the frequency detector output of the (k-1)th received symbol. Since the RDDCR includes the function of PLL loop filter by rotating the decision boundary, it gives a simpler demodulator structure. The rotational decision-directed blind equalization(RDDBE) with the rotated decision boundary based on the Stop-and-Go Algorithm(SGA) operated during tracking the frequency offset by the RDDCR and removes intersymbol interference due to multipaths and channel noise. Test results show that symbol error rate of $10^{-3}$ is obtained before the forward error correction when SNR equals 15dB with 150KHz of carrier frequency offset and two multipaths, which is the channel condition for 32-QAM receiver.