• 제목/요약/키워드: Mean Square Difference

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블럭 정합 알고리즘을 위한 적응적 비트 축소 MAD 정합 기준과 VLSI 구현 (An Adaptive Bit-reduced Mean Absolute Difference Criterion for Block-Matching Algorithm and Its VlSI Implementation)

  • 오황석;백윤주;이흥규
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제27권5호
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    • pp.543-550
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    • 2000
  • 블럭 정합 알고리즘의 VLSI 구현시 복잡도를 줄이고, 수행 속도를 높이기 위하여 새로운 정합 기준인 적응적 비트 축소 MAD(adaptive bit-reduced mean absolute difference:ABRMAD)를 제안한다. ABRMAD는 기존의 MAD에서 화소의 모든 비트를 비교하는 대신, 화소를 구성하는 중요한 비트만을 고려하여 축소된 화소 값을 비교하여 움직임 벡터를 찾는다. 실험을 통하여, 제안한 정합 기준은 기존의 MAD 정합 기준에 비하여 낮은 하드웨어 복잡도를 가지면서 MSE(mean square error) 측면에서 유사한 성능을 가짐을 보인다. 또한 기존의 비트 수 축소형 정합 기준인 DPC(difference pixel counting), BBME(binary-matching with edge-map), 그리고 BPM(bit-plane matching)과 비교하여 같은 수의 비트를 사용하였을 경우 좋은 MSE 성능을 가짐을 보인다.

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양자화 재생레벨 조정을 통한 DCT 영상 코오딩에서의 블록화 현상 감소 방법 (A Quantizer Reconstruction Level Control Method for Block Artifact Reduction in DCT Image Coding)

  • 김종훈;황찬식;심영석
    • 전자공학회논문지B
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    • 제28B권5호
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    • pp.318-326
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    • 1991
  • A Quantizer reconstruction level control method for block artifact reduction in DCT image coding is described. In our scheme, quantizer reconstruction level control is obtained by adding quantization level step size to the optimum quantization level in the direction of reducing the block artifact by minimizing the mean square error(MSE) and error difference(EDF) distribution in boundary without the other additional bits. In simulation results, although the performance in terms of signal to noise ratio is degraded by a little amount, mean square of error difference at block boundary and mean square error having relation block artifact is greatly reduced. Subjective image qualities are improved compared with other block artifact reduction method such as postprocessing by filtering and trasform coding by block overlapping. But the addition calculations of 1-dimensional DCT become to be more necessary to coding process for determining the reconstruction level.

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노이즈 불확실성하에서의 확장칼만필터의 변종들과 코스트 레퍼런스 파티클필터를 이용한 표적추적 성능비교 (Performance Comparison of Various Extended Kalman Filter and Cost-Reference Particle Filter for Target Tracking with Unknown Noise)

  • 신명인;홍우영
    • 한국시뮬레이션학회논문지
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    • 제27권3호
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    • pp.99-107
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    • 2018
  • 본 논문에서는 비선형성을 가지는 측정방정식의 상태값을 효과적으로 추정할 수 있는 확장칼만필터(Extended Kalman Filter/EKF)와 확장칼만필터의 변종들 그리고 코스트 레퍼런스 파티클필터(Cost-Reference Particle Filter/CRPF)를 이용하여 이차원 공간에서 표적추적 성능에 관하여 연구한다. 확장칼만필터의 변종으로 분산점칼만필터(Unscented Kalman Filter/UKF), 중심차분칼만필터(Central Difference Kalman Filter/CDKF), 제곱근 분산점칼만필터(Square Root Unscented Kalman Filter/SR-UKF) 그리고 제곱근 중심차분칼만필터(Square Root Central Difference Kalman Filter/SR-CDKF)를 소개한다. 본 연구에서는 노이즈가 불확실한 표적에 대하여 몬테카를로 시뮬레이션 기법을 이용하여 각 필터들의 평균제곱오차(Mean Square Error/MSE)를 계산하였다. 시뮬레이션 결과 확장칼만필터의 변종들 중에서 제곱근 중심차분칼만필터가 속도와 성능 면에서 가장 우수한 결과를 보여주었다. 코스트 레퍼런스 파티클 필터는 확장칼만필터와 다르게 노이즈의 확률 분포를 알 필요가 없다는 유리한 특성을 가지고 있으며 시뮬레이션 결과 제곱근 중심차분칼만필터보다 처리속도 및 정확도 면에서 우수한 결과를 보여주었다.

모의실험(模擬實驗)에서 반복회수(反復回數)의 연구 (On The Number of Replications in Simulation Study)

  • 송재기
    • Journal of the Korean Data and Information Science Society
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    • 제1권
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    • pp.47-57
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    • 1990
  • A method which determines the number of replications in the simulation is proposed, particularly for small-sample comparison of estimators. This method takes the smallest number of replications that makes the difference of mean square errors be statistically significant and provides an efficient algorithm for calculating the standard error of the mean square error. Two examples are illustrated, the first one is on comparison of mean and median ; the second, the Kaplan-Meier type and Buckley-James type estimators of a quantile function with censored data.

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MEAN-VALUE PROPERTY AND CHARACTERIZATIONS OF SOME ELEMENTARY FUNCTIONS

  • Matkowski, Janusz
    • 대한수학회보
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    • 제50권1호
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    • pp.263-273
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    • 2013
  • A mean-value result, saying that the difference quotient of a differentiable function in a real interval is a mean value of its derivatives at the endpoints of the interval, leads to the functional equation $$\frac{f(x)-F(y)}{x-y}=M(g(x),\;G(y)),\;x{\neq}y$$, where M is a given mean and $f$, F, $g$, G are the unknown functions. Solving this equation for the arithmetic, geometric and harmonic means, we obtain, respectively, characterizations of square polynomials, homographic and square-root functions. A new criterion of the monotonicity of a real function is presented.

박판 정4각튜브의 동적 평균압괴하중 (The Dynamic Mean Crush Load of Thin-walled Square Tubes)

  • 김천욱;한병기;원종진
    • 한국자동차공학회논문집
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    • 제6권5호
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    • pp.119-127
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    • 1998
  • Assuming that the static loaded square tube and the dynamic loaded one have no difference in their characteristics of the crush distance, the theoretical mean dynamic crush load was calculated with respect to the impact speed considering the strain rate sensitivity of the material. The ratio of dynamic to static mean crush load was predicted with previous results. The theoretical analysis was compared with the experimental results of aluminum square tubes axially loaded dynamically.

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메이크헴 수명분포에 의존한 소프트웨어 평균고장간격시간에 관한 모수 추정법 비교 연구 (A Comparative Study of the Parameter Estimation Method about the Software Mean Time Between Failure Depending on Makeham Life Distribution)

  • 김희철;문송철
    • Journal of Information Technology Applications and Management
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    • 제24권1호
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    • pp.25-32
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    • 2017
  • For repairable software systems, the Mean Time Between Failure (MTBF) is used as a measure of software system stability. Therefore, the evaluation of software reliability requirements or reliability characteristics can be applied MTBF. In this paper, we want to compare MTBF in terms of parameter estimation using Makeham life distribution. The parameter estimates used the least square method which is regression analyzer method and the maximum likelihood method. As a result, the MTBF using the least square method shows a non-decreased pattern and case of the maximum likelihood method shows a non-increased form as the failure time increases. In comparison with the observed MTBF, MTBF using the maximum likelihood estimation is smallerd about difference of interval than the least square estimation which is regression analyzer method. Thus, In terms of MTBF, the maximum likelihood estimation has efficient than the regression analyzer method. In terms of coefficient of determination, the mean square error and mean error of prediction, the maximum likelihood method can be judged as an efficient method.

진폭비 불일치에 의한 cross-eye 재밍 성능: 각도 추적 오차 성능 분석 비교 (Performance of cross-eye jamming due to amplitude mismatch: Comparison of performance analysis of angle tracking error)

  • 김제안;김진성;이준호
    • 융합정보논문지
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    • 제11권11호
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    • pp.51-56
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    • 2021
  • 본 논문에서는 cross-eye의 두 재밍 안테나의 진폭 불일치로 인한 성능 저하를 고려한다. 진폭비의 불일치는 기계적 결함에 따른 실제 진폭비와 명목상 진폭비의 차이가 정규분포를 갖는 랜덤변수로 모델링한다. 1차 테일러 전개와 2차 테일러 전개를 통한 해석적 성능분석이 제안된다. 실제 진폭비와 명목상 진폭비의 불일치가 발생한 Cross-eye 재밍의 성능 측정은 mean square difference (MSD)를 계산함으로서 측정된다. 해석적으로 유도된 MSD는 1차 테일러 전개 기반 시뮬레이션 기반 MSD 및 2차 테일러 전개 기반 시뮬레이션 기반 MSD와 해석 기반 MSD와 비교함으로써 검증된다. 계산비용이 높은 Monte-Carlo기반 MSD보다 해석 기반 MSD가 우수함을 보인다.

An improved estimation procedure of population mean using bivariate auxiliary information under non-response

  • Bhushan, Shashi;Pandey, Abhay Pratap
    • Communications for Statistical Applications and Methods
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    • 제26권4호
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    • pp.347-357
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    • 2019
  • We propose new classes of estimators of population mean under non-response using bivariate auxiliary information. Some improved regression (or difference) type estimators have been proposed in four different situations of non response along with their properties and the expressions for the bias and mean square errors of the proposed estimators are derived under double (two-stage) sampling scheme. The properties of the suggested class of estimators are studied and it is observed that the proposed estimators performed better when compared to conventional estimators proposed by Singh and Kumar (Journal of Statistical Planning and Inference, 140, 2536-2550, 2010b), Shabbir and Khan (Communications in Statistics - Theory and Methods, 42, 4127-4145, 2013) and Bhushan and Naqvi (Journal of Statistics and Management Systems, 18, 573-602, 2015). A comparative study is also conducted both theoretically as well as empirically in order to support the results.

Mean estimation of small areas using penalized spline mixed-model under informative sampling

  • Chytrasari, Angela N.R.;Kartiko, Sri Haryatmi;Danardono, Danardono
    • Communications for Statistical Applications and Methods
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    • 제27권3호
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    • pp.349-363
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    • 2020
  • Penalized spline is a suitable nonparametric approach in estimating mean model in small area. However, application of the approach in informative sampling in a published article is uncommon. We propose a semiparametric mixed-model using penalized spline under informative sampling to estimate mean of small area. The response variable is explained in terms of mean model, informative sample effect, area random effect and unit error. We approach the mean model by penalized spline and utilize a penalized spline function of the inclusion probability to account for the informative sample effect. We determine the best and unbiased estimators for coefficient model and derive the restricted maximum likelihood estimators for the variance components. A simulation study shows a decrease in the average absolute bias produced by the proposed model. A decrease in the root mean square error also occurred except in some quadratic cases. The use of linear and quadratic penalized spline to approach the function of the inclusion probability provides no significant difference distribution of root mean square error, except for few smaller samples.