• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.27-33
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• 2000

Gardner’s algorithm is one of the useful algorithm for NDD(Non-Decision Directed) symbol synchronization in PAM communications. But the algorithm has a weak point such as pattern noises increasing in multi-level PAM. To insert a pre-filter in the algorithm is able to reduce timing jitter and pattern noise. In this paper, we analyze statistical properties of NDD algorithm to find an optimal parameter of the pre-filter for improving timing jitter and PLL locking. As a simulation result, optimum value of pre-filter parameter, $\beta$, is 0.3 and 0.5 at the roll off factor of the channel, $\alpha$, is 0.5 and 1.0, respectively. Optimum parameters of the pre-filter for clock synchronization of all-digital 256-QAM demodulator is shown in the results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1045-1051
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• 2003

The SOVA, which produces the soft decision value, can be used as a sub-optimum solution for concatenated codes such as turbo codes, since it is computationally efficient compared with the optimum MAP algorithm. In this paper, we propose an efficient implementation of the SOVA used for decoding turbo codes, by reducing the number of calculations for soft decision values and trace-back operations. In order to utilize the memory efficiently, the whole block of turbo codes is divided into several sub-blocks in the proposed algorithm. It is demonstrated that the proposed algorithm requires less computation than the conventional algorithm, while providing the same overall performance.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.891-893
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• 1997

In this paper an intelligent power transformer protective relaying algorithm based on Fuzzy Decision-Making is presented. The introduced protection algorithm contains several internal fuzzy rule-bases including bpa(Basic Probability Assignment: m) which are subject to off-line pre-installation by the analysis of the transformer transient characteristics for detecting the internal fault. Dempster-Shafer's rule of combination is used for the inference method with rules to decide the situation of a transformer, The proposed algorithm immunes to the saturation of transformer, inrush conditions, over excitation, and external fault. The included results of testing show practically sufficient sensitivity and selectivity of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10B
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• pp.1210-1215
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• 2011

In this paper, a supervised adaptive equalization algorithm based on probability density function (PDF) matching method is introduced and its decision-feedback version is proposed for underwater communication channels with strong impulsive noise and severe multipath characteristics. The conventional least mean square (LMS) algorithm based on mean squared error (MSE) criterion has shown to be incapable of coping with impulsive noise and multipath effects commonly shown in underwater communications. The linear PDF matching algorithm, which shows immunity to impulsive noise, however, has revealed to yield unsatisfying performance under severe multipath environments with impulsive noise. On the other hand, the proposed nonlinear PDF matching algorithm with decision feedback proves in the simulation to possess superior robustness against impulsive noise and multipath characteristics of underwater communication channels.

• International Journal of Highway Engineering
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• v.18 no.5
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• pp.105-115
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• 2016

PURPOSES : This study was initiated to analyze the characteristics of bus traffic accidents, by bus types, using the decision tree in order to establish customized safety alternatives by bus types, including the intra-city bus, rural area bus, and inter-city bus. METHODS : In this study, the major elements involved in bus traffic accidents were identified using decision trees and CHAID algorithm. The decision tree was used to identify the characteristics of major elements influencing bus traffic accidents. In addition, the CHAID algorithm was applied to branch the decision trees. RESULTS : The number of casualties and severe injuries are high in bus accidents involving pedestrians, bicycles, motorcycles, etc. In the case of light injury caused by bus accidents, different results are found. In the case of intra-city bus accidents, the probability of light injury is of 77.2% when boarding a non-owned car and breaching of duty to drive safely are involved. In the case of rural area bus accidents, the elements showing the highest probability of light injury are boarding an owned car, vehicle-to-vehicle accidents, and breaching of duty to drive safely. In the case of intra-city bus accidents, boarding owned car, streets, and vehicle-to-vehicle accidents work as the critical elements. CONCLUSIONS : In this study, the bus accident data were categorized by bus types, and then the influential elements were identified using decision trees. As a result, the characteristics of bus accidents were found to be different depending on bus types. The findings in this study are expected to be utilized in establishing effective alternatives to reduce bus accidents.

• Journal of Korea Game Society
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• v.11 no.6
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• pp.61-70
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• 2011

In this paper, we propose a defense NPC control model in the soccer game by applying the Decision Tree learning algorithm. The proposed model extracts the direction patterns and the action patterns generated by many soccer game users, and applies these patterns to the Decision Tree learning algorithm. Then, the proposed model decides the direction and the action according to the learned Decision Tree. Experimental results show that the proposed model takes some time to learn the Decision Tree while the proposed model takes 0.001-0.003 milliseconds to decide the direction and the action based on the learned Decision Tree. Therefore, the proposed model can control NPC in the soccer game system in real time. Also, the proposed model achieves higher accuracy than a previous model (Letia98); because the proposed model can utilize current state information, its analyzed information, and previous state information.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.12-21
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• 1998

In this paper, we describe the one channel five-way, V/U/M/N/S (Voice/Unvoice/Nasal/Silent), classification algorithm for automatically classifying speech. The decision making process is viewed as a pattern viewed as a pattern recognition problem. Two aspects of the algorithm are developed: feature selection and classifier type. The feature selection procedure is studied for identifying a set of features to make V/U/M/N/S classification. The classifiers used are a vector quantization (VQ), a neural network(NN), and a decision tree method. Actual five sentences spoken by six speakers, three male and three female, are tested with proposed classifiers. From a set of measurement tests, the proposed classifiers show fairly good accuracy for V/U/M/N/S decision.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.9
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• pp.402-412
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• 2002

The navigation algorithms enable autonomous mobile robots to reach given target points without collision against obstacles. To achieve safe navigations in unknown environments, this paper presents an effective navigation algorithm for the autonomous mobile robots with ultrasonic sensors. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The fuzzy-based decision maker combines the steering angles from the target-reaching behavior and the obstacle-avoidance behavior in order to steer the autonomous mobile robot appropriately. Simulational and experimental results show that the proposed navigation algorithm is very effective in unknown environments.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.455-465
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• 2006

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, and relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. We analyze industrial waste database using data mining technique. We use k-means algorithm for clustering and C5.0 algorithm for decision tree and Apriori algorithm for association rule. We can use these outputs for environmental preservation and environmental improvement.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.12
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• pp.1333-1339
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• 2009

A MWR(Missile Warning Radar) of GVES(Ground Vehicle Equipment System) has to effectively decide the threat for a detected target. Linear Approximation Fitting(LAF) and Weighted Linear Approximation Fitting(WLAF) algorithm is proposed as algorithm for a threat decision method. The target is classified into a threat or non-threat using a boundary condition of the angular rate, and the boundary condition is determined using probability model simulation. This paper confirms the performance of proposed threat decision algorithm using measurement.