• Title/Summary/Keyword: Mean vector

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ON SLANT RIEMANNIAN SUBMERSIONS FOR COSYMPLECTIC MANIFOLDS

  • Erken, Irem Kupeli;Murathan, Cengizhan
    • Bulletin of the Korean Mathematical Society
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    • v.51 no.6
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    • pp.1749-1771
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    • 2014
  • In this paper, we introduce slant Riemannian submersions from cosymplectic manifolds onto Riemannian manifolds. We obtain some results on slant Riemannian submersions of a cosymplectic manifold. We also give examples and inequalities between the scalar curvature and squared mean curvature of fibres of such slant submersions in the cases where the characteristic vector field is vertical or horizontal.

A Variable Size Block Matching Algorithm Using Local Characteristics of Images (영상의 국부적 성질을 이용한 가변 크기 블록 정합 알고리즘)

  • 김진태;최종수;박래홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.7
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    • pp.62-69
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    • 1992
  • The conventional BMA is performed with the fixed block size. For better performance at low bitrate, the block size is required to be large in relatively stationary area, while small in moving area. Thus, in this paper, a video coding technique using variable block size model is proposed. It decides the block size based on the degree of local motion defined by the local mean and variance of blocks. Computer simulation shows that the proposed method gives comparable performance to the conventional one with less bits required for motion vector coding.

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Properties of variable sampling interval control charts

  • Chang, Duk-Joon;Heo, Sun-Yeong
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.4
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    • pp.819-829
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    • 2010
  • Properties of multivariate variable sampling interval (VSI) Shewhart and CUSUM charts for monitoring mean vector of related quality variables are investigated. To evaluate average time to signal (ATS) and average number of switches (ANSW) of the proposed charts, Markov chain approaches and simulations are applied. Performances of the proposed charts are also investigated both when the process is in-control and when it is out-of-control.

Accuracy of Multiple Outlier Tests in Nonlinear Regression

  • Kahng, Myung-Wook
    • Communications for Statistical Applications and Methods
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    • v.18 no.1
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    • pp.131-136
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    • 2011
  • The original Bates-Watts framework applies only to the complete parameter vector. Thus, guidelines developed in that framework can be misleading when the adequacy of the linear approximation is very different for different subsets. The subset curvature measures appear to be reliable indicators of the adequacy of linear approximation for an arbitrary subset of parameters in nonlinear models. Given the specific mean shift outlier model, the standard approaches to obtaining test statistics for outliers are discussed. The accuracy of outlier tests is investigated using subset curvatures.

Multivariate Control Charts for Several Related Quality Characteristics

  • Chang, Duk-Joon;Shin, Jae-Kyoung
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.2
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    • pp.467-476
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    • 2005
  • Multivariate control charts for monitoring mean vector of several related quality variables with combine-accumulate approach and accumulate-combine apprach were investigated. Shewhart chart is also proposed to compare the performances of CUSUM and EWMA charts. Numerical comparisons show that CUSUM and EWMA charts are more efficient than Shewhart chart for small or moderate shifts, and multivariate charts based on accumulate- combine approach is more efficient than corresponding multivariate charts based on combine-accumulate approach.

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Kernel Machine for Poisson Regression

  • Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.3
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    • pp.767-772
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    • 2007
  • A kernel machine is proposed as an estimating procedure for the linear and nonlinear Poisson regression, which is based on the penalized negative log-likelihood. The proposed kernel machine provides the estimate of the mean function of the response variable, where the canonical parameter is related to the input vector in a nonlinear form. The generalized cross validation(GCV) function of MSE-type is introduced to determine hyperparameters which affect the performance of the machine. Experimental results are then presented which indicate the performance of the proposed machine.

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An Optimality Criterion for Median-unbiased Estimators

  • Sung, Nae-Kyung
    • Journal of the Korean Statistical Society
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    • v.19 no.2
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    • pp.176-181
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    • 1990
  • Sung [1990] presented an analogue of the classical Cramer-Rao inequality for median-unbiased estimators with continuous multivariate densities depending upon a vector parameter. In the process, diffusivity, a new dispersion measure relevant to median-unbiased estimators, was defined to be a function of median-unbiased estimator's density height. In this paper we shall elaborate these ideas by defining a second kind of diffusivity and discuss the role of model-unbiasedness in median-unbiased estimation in connection with this seconde kind of diffusivity. In addition, median-unbiased estimation will be compared to mean-unbiased estimation.

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Moving Object Tracking Method in Video Data Using Color Segmentation (칼라 분할 방식을 이용한 비디오 영상에서의 움직이는 물체의 검출과 추적)

  • 이재호;조수현;김회율
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.219-222
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    • 2001
  • Moving objects in video data are main elements for video analysis and retrieval. In this paper, we propose a new algorithm for tracking and segmenting moving objects in color image sequences that include complex camera motion such as zoom, pan and rotating. The Proposed algorithm is based on the Mean-shift color segmentation and stochastic region matching method. For segmenting moving objects, each sequence is divided into a set of similar color regions using Mean-shift color segmentation algorithm. Each segmented region is matched to the corresponding region in the subsequent frame. The motion vector of each matched region is then estimated and these motion vectors are summed to estimate global motion. Once motion vectors are estimated for all frame of video sequences, independently moving regions can be segmented by comparing their trajectories with that of global motion. Finally, segmented regions are merged into the independently moving object by comparing the similarities of trajectories, positions and emerging period. The experimental results show that the proposed algorithm is capable of segmenting independently moving objects in the video sequences including complex camera motion.

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