• 대한전자공학회논문지SP
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• 제44권6호
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• pp.54-62
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• 2007

본 논문에서는 기존의 고속 인트라 4$\times$4 예측 모드 선택 알고리즘을 인트라 16$\times$16 예측에 적용하여 연산량을 감소시키고, 변환 계수의 일부분만을 사용하여 인트라 16$\times$16 예측 모드 선택을 고속으로 수행하는 방법을 제안한다. 제안하는 방법은 기준 블록과 예측 블록간의 차분에 4$\times$4 변환을 수행한 후 DC계수 하나와 주변의 AC계수 3개만을 사용하여 모드 선택을 수행한다. 이론적인 분석과 실험적 결과를 통해서 제안한 방법을 사용하여 인트라 16$\times$16 예측 모드 선택을 수행할 경우 부호화효율의 큰 감소 없이 필요한 연산량을 50%까지 줄일 수 있었다.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.845-857
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• 2003

We explore the use of genetic programming to evolve decision trees directly for classification problems with both discrete and continuous predictors. We demonstrate that the derived hypotheses of standard algorithms can substantially deviated from the optimum. This deviation is partly due to their top-down style procedures. The performance of the system is measured on a set of real and simulated data sets and compared with the performance of well-known algorithms like CHAID, CART, C5.0, and QUEST. Proposed algorithm seems to be effective in handling problems caused by top-down style procedures of existing algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.477-477
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• 2000

A multifunctional sensor is designed to measure viscosity, cleanness, temperature and capacitance of engine oil to make a clear decision on its condition. The simple structure helps easy fabrication and low cost while measuring four parameters by one sensor. The operation is described theoretically and is supported by experimental data. A fuzzy based algorithm to fuse the four kinds of data from multi-functional sensor in order to make a decision on the best time to change the oil is proposed.

• 한국음향학회지
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• 제28권3호
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• pp.285-289
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• 2009

본 논문에서는 음향학적 반향 제거(AES, acoustic echo suppression)를 위해 주파수영역에서 soft decision 기법에 근거한 새로운 동시통화 검출 (DTD, double-talk detection) 알고리즘을 제안한다. 제시된 방법은 효과적인 DTD를 위해 상관계수 (cross-correlation coefficient)에 기반하여 hard decision을 사용하는 기존의 알고리즘 대신 주파수 영역에서 입력 및 원단신호의 VAD (voice activity detection) 결과와 음성 통계모델에 기반한 soft decision 방법을 도입하여 전역 근단화자존 재확률 (GNSPP, global near-end speech presence probability)을 DTD에 적용한다. 제안된 알고리즘은 기존의 방법과 객관적인 실험을 통해 비교 평가한 결과 다양한 배경잡음 환경에서 우수한 성능을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.227-230
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• 1997

In this paper, robot navigation experiments with a new navigation algorithm are carried out in real environments. The authors already proposed a reactive navigation algorithm for mobile robots using optimal via-point selection method. At each sampling time, a number of via-point candidates is constructed with various candidates of heading angles and velocities. The robot detects surrounding obstacles, and the proposed algorithm utilizes fuzzy multi-attribute decision making in selecting the optimal via-point the robot would proceed at next step. Fuzzy decision making allows the robot to choose the most qualified via-point even when the two navigation goals-obstacle avoidance and target point reaching-conflict each other. The experimental result shows the successful navigation can be achieved with the proposed navigation algorithm for real environments.

• 전자공학회논문지B
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• 제33B권6호
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• pp.102-110
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• 1996

A new design scheme of a binary decision tree is proposed. In this scheme a binary decision tree is constructed by using genetic algorithm and FCM algorithm. At each node optimal or near-optimal feature subset is selected which optimizes fitness function in genetic algorithm. The fitness function is inversely proportional to classification error, balance between cluster, number of feature used. The binary strings in genetic algorithm determine the feature subset and classification results - error, balance - form fuzzy partition matrix affect reproduction of next genratin. The proposed design scheme is applied to the tire tread patterns and handwriteen alphabetic characters. Experimental results show the usefulness of the proposed scheme.

• Journal of Communications and Networks
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• 제15권5호
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• pp.486-495
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• 2013

In this article, we suggest a two-dimensional genetic algorithm (GA) method that applies a cognitive radio (CR) decision engine which determines the optimal transmission parameters for multicarrier communication systems. Because a CR is capable of sensing the previous environmental communication information, CR decision engine plays the role of optimizing the individual transmission parameters. In order to obtain the allowable transmission power of multicarrier based CR system demands interference analysis a priori, for the sake of efficient optimization, a two-dimensionalGA structure is proposed in this paper which enhances the computational complexity. Combined with the fitness objective evaluation standard, we focus on two multi-objective optimization methods: The conventional GA applied with the multi-objective fitness approach and the non-dominated sorting GA with Pareto-optimal sorting fronts. After comparing the convergence performance of these algorithms, the transmission power of each subcarrier is proposed as non-interference emission with its optimal values in multicarrier based CR system.

• 대한전자공학회논문지
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• 제27권2호
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• pp.9-15
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• 1990

本 論文에서는 線刑 2元 블럭 符號에 대한 軟判定 復號 알고리듬을 제안하였다. 이 알고리듬은 블록 誤謬 確率을 最小化하기 위한 것이다. 提案된 알고리듬을 기存의 다른 復號法과 비교하기 위하여(7,4) Hamming 符號와(23,12)Golay 符號에 대한 컴퓨터 시뮬레이션을 수행하였다. 그 결과, 提案된 알고리듬의 乎均 硬判定 復號 回數는 항상 2以下이며 信號對 雜音比가 충분히 클때 1에 접근하였다. 즉, 기存 다른 復號法에 비하여 復號의 複雜度가 減少되었음을 확인하였다.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.195-205
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• 2005

In decision tree analysis, C4.5 and CART algorithm have some problems of computational complexity and bias on variable selection. But QUEST algorithm solves these problems by dividing the step of variable selection and split point selection. When input variables are continuous, QUEST algorithm uses ANOVA F-test under the assumption of normality and homogeneity of variances. In this paper, we investigate the influence of violation of normality assumption and effect of the transformation of variables in the QUEST algorithm. In the simulation study, we obtained the empirical powers of variable selection and the empirical bias of variable selection after transformation of variables having various type of underlying distributions.

• 전자공학회논문지C
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• 제35C권3호
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• pp.69-78
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• 1998

This paper presented a method of extracting algorithm for Edge Multiple-Valued Decision Diagrams(EMVDD), a new data structure, from Binary Decision Diagram(BDD) which is resently using in constructing the digital logic systems based on the graph theory. We discussed the function minimization method of the n-variables multiple-valued functions and showed that the algorithm had the regularity with module by which the same blocks were made concerning about the schematic property of the proposed algorithm. We showed the EMVDD of Full Adder by module construction and verified the proposed algorithm by examples. The proposed method has the visible, schematical and regular properties.