• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.54-62
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• 2007

In this paper, we significantly reduces the amount of computation for intra 16$\times$16 mode decision in H.264 by applying the fast algorithm, which obtains the transformed prediction residual with fewer computations. By extending the existing intra 4$\times$4 mode decision, we propose the new algorithm for fast intra 16$\times$16 mode decision. The proposed algorithm uses partial transform coefficients which consist of one DC and three adjacent AC coefficients after 4$\times$4 transform in the intra 16$\times$16 mode decision. Theoretical analysis and experimental results show that the proposed algorithm can reduce computations up to 50% in the intra 16$\times$16 mode decision process with unnoticeable degradation.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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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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• 2000.10a
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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.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.285-289
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• 2009

In this paper, we propose a novel double-talk detection (DTD) technique based on soft decision in the frequency domain. In the proposed method, global near-end speech presence probability (GNSPP) considering the statistical model assumption and voice activity detection (VAD) decision of the near-end and far-end signal are applied to the DTD algorithm in the frequency domain instead of the traditional hard decision scheme using cross-correlation coefficients. The performance of the proposed algorithm is evaluated by the objective test under various environments, and yields better results compared with the conventional scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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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.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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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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• v.15 no.5
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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.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.2
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• pp.9-15
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• 1990

A soft-decision decoding algorithm for linear binary block codes is proposed, for minimizing the block error probability. To compare the proposed algorithm with already established decoding methods, computer simulations are performed for the (7,4)Hamming code and the (23,12) Golay code. The average number of hard-decision decoding is always less then 2, and approaches to 1 when the signal to noise ratio is sufficiently large. These results show that the proposed algorithm reduces the decoding complexity.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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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.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.3
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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.