• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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• pp.188-190
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• 2011

Image interpolation is a technique that pervades many an application. Interpolation is almost never the goal in itself, yet it affects both the desired results and the ways to obtain them. In this paper, we proposed a technique that is capable to find out the error when the common two methods (bilinear and nearest neighbor interpolation) are applied on an image for rotation. The proposed technique also includes the comparison results of bilinear interpolation and nearest neighbor interpolation. Among them nearest neighbor interpolation gives us a better result regarding to the enhancement and due to least error. The error is found by using Mean Square Error (MSE).

• 한국통신학회논문지
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• 제21권6호
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• pp.1546-1553
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• 1996

The bit error probability of RS/trellis concatenated coded-modualtion system in the mobile radio channel is analyzed. A new upper bound to the symbol error probability of the inner TCM in the mobile radio channel is obtained by exploiting the unequal symbol error probability of the TCM. This bound is applied to the derivation of the upper bound to the bit error probability of the concatenated coded-modulation system. An efficient way of searching distance spectrum of the TCM in mobile radio channel is devised. Our new bounds are tighter than the earlier studied other bounds.

• 한국통신학회논문지
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• 제17권9호
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• pp.1020-1028
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• 1992

본 논문에서는 TCM(Trellis Coded Modulation)에서 연집에러 검출 및 최대 확률론적 복호 방식으로 구성된 연집에러 정정을 위한 적응 복호방식을 제시하고 있다. 복호기는 보통 비터비 복호기로서 동작하고, 미터비 복호기에 의해 정정될 수 없는 에러가 검출될 경우 연집 에러 정정 모드로 절환된다. 이동통신에서의 채널특성인 연집에러가 빈번히 발생하는 다경로 페이딩 채널에서 적응 복호방식을 이용한 TCM은 기존의 방식에 비해 비트오율면에서 향상된 성능을 나타내고 있다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.258-258
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• 2018

In this study, a hydraulic flow model and an error correction model are combined to improve the flood simulation accuracy. First, the hydraulic flow model is calibrated by optimizing the Manning's roughness coefficient that considers spatial and temporal variability. Then, an error correction model were used to correct the systematic errors of the calibrated hydraulic model. The error correction model is developed using Artificial Neural Networks (ANNs) that can estimate the systematic simulation errors of the hydraulic model by considering some state variables as inputs. The input variables are selected using parital mutual information (PMI) technique. It was found that the calibrated hydraulic model can simulate flood water levels with good accuracy. Then, the accuracy of estimated flood levels is improved further by using the error correction model. The method proposed in this study can be used to the flood control and water resources management as it can provide accurate water level eatimation.

• 디지털산업정보학회논문지
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• 제10권4호
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• pp.53-61
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• 2014

In this paper, we proposed covariance weight matrix using SPT matrix in order to accurate target estimation. We have estimated a target using modified covariance matrix and beam steering error method. We have minimized beam steering error in order to estimation desired a target. This method obtain optimum covariance weight using modified SPT matrix. This paper of proposal method is showed good performance than general method. We updated a weight of covariance matrix using modified SPT matrix. We obtain optimum covariance matrix weight to application beam steering error method in order to beam steering toward desired target. Through simulation, we showed that compare proposal method with general method. It have improved resolution of estimation target to good performance more proposed method than general method.

• 한국통신학회논문지
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• 제26권8A호
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• pp.1322-1328
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• 2001

본 논문에서는 무선 ATM 환경에서 터보코딩을 이용한 UEP(Unequal Error Protection)을 제안한다. 일반적으로 ATM셀의 header 부분은 payload 부분보다 중요시되며 header 부분에 payload 보다 부호율이 낮은 터보코드를 무선 ATM 적용하여 비트오류확률과 셀손실 확률을 구하였다. 무선 ATM 환경에서 터보코드를 사용하고 프레임길이 28바이트의 DLC 셀구조에서 UEP가 가능함을 보였다. 부호율 1/3인 터보 코딩을 이용한 경우 동일한 부호율의 컨벌루션 코드를 이용한 EEP(Equal Error Protection)과 비교하여 비트 오류확률과 셀 손실율에 있어서 최소 1dB와 2dB 신호대잡음비의 개선을 보였다.

• Journal of the Korean Data and Information Science Society
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• 제20권4호
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• pp.757-764
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• 2009

In discriminant analysis, we consider a special pattern which contains a block of missing observations. We assume that the two populations are equally likely and the costs of misclassification are equal. In this situation, we consider the bootstrap confidence intervals of the error rate in the circular models when the covariance matrices are equal and not equal.

• Journal of the Korean Data and Information Science Society
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• 제7권1호
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• pp.87-92
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• 1996

A regression model with nested erroe structure is considered. The regression model includes two error terms that are independent and normally distributed with zero means and constant variances. This error structure of the model gives correlated response variables. The distributions of variance components in the regression model with nested error structure are dervied by using theorems for quadratic forms.

• Journal of the Korean Data and Information Science Society
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• 제9권2호
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• pp.165-172
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• 1998

This paper considers a linear regression model with censored data where each error term follows a multivariate normal distribution. In this paper we consider the diffuse prior distribution for parameters of the linear regression model. With censored data we derive the full conditional densities for parameters of a multiple regression model in order to obtain the marginal posterior densities of the relevant parameters through the Gibbs Sampler, which was proposed by Geman and Geman(1984) and utilized by Gelfand and Smith(1990) with statistical viewpoint.

• Journal of information and communication convergence engineering
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• 제6권2호
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• pp.134-139
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• 2008

In this paper, we propose an analysis model for the performance of channel error probability in Stream Control Transmission Protocol (SCTP) using Markov model. In this model it is assumed that the compressor and decompressor work in Unidirectional Mode. And the average throughput of SCTP protocol is obtained by finding the throughputs of when the initial channel state is good or bad.