• Title/Summary/Keyword: simulation extrapolation

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Whole Frame Error Concealment with an Adaptive PU-based Motion Vector Extrapolation for HEVC

  • Kim, Seounghwi;Lee, Dongkyu;Oh, Seoung-Jun
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.1
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    • pp.16-21
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    • 2015
  • Most video services are transmitted in wireless networks. In a network environment, a packet of video is likely to be lost during transmission. For this reason, numerous error concealment (EC) algorithms have been proposed to combat channel errors. On the other hand, most existing algorithms cannot conceal the whole missing frame effectively. To resolve this problem, this paper proposes a new Adaptive Prediction Unit-based Motion Vector Extrapolation (APMVE) algorithm to restore the entire missing frame encoded by High Efficiency Video Coding (HEVC). In each missing HEVC frame, it uses the prediction unit (PU) information of the previous frame to adaptively decide the size of a basic unit for error concealment and to provide a more accurate estimation for the motion vector in that basic unit than can be achieved by any other conventional method. The simulation results showed that it is highly effective and significantly outperforms other existing frame recovery methods in terms of both objective and subjective quality.

Recovery of Truncated Projection using Non-iterative Extrapolation and Improvement of Image (비반복 외삽법에 의한 불완전 투명 데이터의 재생 및 영상의 개선법)

  • Lee, Gang-Ho;Choe, Jong-Ho;Choe, Jong-Su
    • Journal of Biomedical Engineering Research
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    • v.8 no.2
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    • pp.151-160
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    • 1987
  • An algorithm is suggested that truncted projection among the incomplete projections can be recovered from non-iterative extrapolation matrix by band-limited function. After the image being reconstructed from the recovered signals by non-iterative extrapolation, a known controur information and reprojection algorithm are used. It is shown that the reconstructed image using these algorithms is close to the original image. The effectiveness for these algorithms is proved by computer simulation.

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Assessment of RMR with the Monte Carlo Simulation and Stability Analysis of Rock Slopes (Monte Carlo Simulation 기법을 이용한 RMR의 역산 및 그에 의한 암반시면의 안정성 분석)

  • 최성웅;정소걸
    • Tunnel and Underground Space
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    • v.14 no.2
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    • pp.97-107
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    • 2004
  • Various kinds of rock mass properties, which can be obtained from laboratory tests as well as field tests, can be reasonably applied to the design of earth structures. An extrapolation technique can be used for this application and it generally guarantee its quality from a sufficient amount of test results because it is based on the RMR value in most cases. When the confident RMR can not be obtained because of the insufficient testing results, the Monte Carlo Simulation technique can be introduced fer deducing the proper RMR and this assessed RMR can be reused fur the major input parameters. Authors' proposed method can be verified from the comparison between the results of numerical analysis and the evidences of field site.

Managing the Reverse Extrapolation Model of Radar Threats Based Upon an Incremental Machine Learning Technique (점진적 기계학습 기반의 레이더 위협체 역추정 모델 생성 및 갱신)

  • Kim, Chulpyo;Noh, Sanguk
    • The Journal of Korean Institute of Next Generation Computing
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    • v.13 no.4
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    • pp.29-39
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    • 2017
  • Various electronic warfare situations drive the need to develop an integrated electronic warfare simulator that can perform electronic warfare modeling and simulation on radar threats. In this paper, we analyze the components of a simulation system to reversely model the radar threats that emit electromagnetic signals based on the parameters of the electronic information, and propose a method to gradually maintain the reverse extrapolation model of RF threats. In the experiment, we will evaluate the effectiveness of the incremental model update and also assess the integration method of reverse extrapolation models. The individual model of RF threats are constructed by using decision tree, naive Bayesian classifier, artificial neural network, and clustering algorithms through Euclidean distance and cosine similarity measurement, respectively. Experimental results show that the accuracy of reverse extrapolation models improves, while the size of the threat sample increases. In addition, we use voting, weighted voting, and the Dempster-Shafer algorithm to integrate the results of the five different models of RF threats. As a result, the final decision of reverse extrapolation through the Dempster-Shafer algorithm shows the best performance in its accuracy.

RICHARDSON EXTRAPOLATION AND DEFECT CORRECTION OF MIXED FINITE ELEMENT METHODS FOR ELLIPTIC OPTIMAL CONTROL PROBLEMS

  • Chen, Yanping;Huang, Yunqing;Hou, Tianliang
    • Journal of the Korean Mathematical Society
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    • v.49 no.3
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    • pp.549-569
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    • 2012
  • In this paper asymptotic error expansions for mixed finite element approximations to a class of second order elliptic optimal control problems are derived under rectangular meshes, and the Richardson extrapolation of two different schemes and interpolation defect correction can be applied to increase the accuracy of the approximations. As a by-product, we illustrate that all the approximations of higher accuracy can be used to form a class of a posteriori error estimators of the mixed finite element method for optimal control problems.

Error Analysis and Compensation of Measurement Delay in INS/GPS Integrated Systems with Kalman Filtering (칼만필터를 사용하는 INS/GPS 결합시스템에서 측정치 지연에 의한 오차 분석 및 보상)

  • Park, Chan-Gook;Cho, Seong-Yun;Jin, Yong
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.11
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    • pp.1039-1044
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    • 2000
  • In this paper, the error caused by the measurement delay in INS/GPS integrated systems with Kalman filtering is defined and analyzed through the analytical method and the simulation. It is proved that the error of measurement delay causes not only the position error but also the estimate error of the x-axis accelerometer bias when a vehicle turns. And the estimation method of the delay time and the compensation method using an extrapolation method are presented. The performance of the compensation method is shown by the analytic method and the simulation.

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Statistical analysis of KNHANES data with measurement error models

  • Hwang, Jinseub
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.3
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    • pp.773-779
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    • 2015
  • We study a statistical analysis about the fifth wave data of the Korea National Health and Nutrition Examination Survey based on linear regression models with measurement errors. The data is obtained from a national population-based complex survey. To demonstrate the availability of measurement error models, two results between the general linear regression model and measurement error model are compared based on the model selection criteria which are Akaike information criterion and Bayesian information criterion. For our study, we use the simulation extrapolation algorithm for measurement error model and the jackknife method for the estimation of standard errors.

SOME PROPERTIES OF SIMEX ESTIMATOR IN PARTIALLY LINEAR MEASUREMENT ERROR MODEL

  • Meeseon Jeong;Kim, Choongrak
    • Journal of the Korean Statistical Society
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    • v.32 no.1
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    • pp.85-92
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    • 2003
  • We consider the partially linear model E(Y) : X$^{t}$ $\beta$+η(Z) when the X's are measured with additive error. The semiparametric likelihood estimation ignoring the measurement error gives inconsistent estimator for both $\beta$ and η(.). In this paper we suggest the SIMEX estimator for f to correct the bias induced by measurement error, and explore its properties. We show that the rational linear extrapolant is proper in extrapolation step in the sense that the SIMEX method under this extrapolant gives consistent estimator It is also shown that the SIMEX estimator is asymptotically equivalent to the semiparametric version of the usual parametric correction for attenuation suggested by Liang et al. (1999) A simulation study is given to compare two variance estimating methods for SIMEX estimator.

Numerical Simulation of Thermal Lattice Boltzmann Model with a Modified In-Ternal Energy Non-Equilibrium First-Order Extrapolation Boundary Condition (수정된 내부 에너지 비평형 1차 외삽 경계조건을 적용한 열 유동 격자 볼츠만 모델에 관한 수치적 연구)

  • Jeong, Hae-Kwon;Kim, Lae-Sung;Lee, Hyun-Goo;Lee, Jae-Ryong;Ha, Man-Yeong
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.31 no.7 s.262
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    • pp.620-627
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    • 2007
  • In this paper, we adapt a modified internal energy non-equilibrium first-order extrapolation thermal boundary condition to the thermal lattice Boltzmann model (TLBM). This model is the double populations approach to simulate hydrodynamic and thermal fields. The bounce-back boundary condition which is a traditional boundary condition of lattice Boltzmann method has only a first order in numerical accuracy at the boundary and numerical instability. A non-equilibrium first-order extrapolation boundary condition has been verified to be of better numerical stability than the bounce-back boundary condition and this boundary condition is proved to be of second-order accuracy for the flat boundaries. The two-dimensional natural convection flow in a square cavity with Pr=0.71 and various Rayleigh numbers are simulated. The results are found to be in good agreement with those of previous studies.

Side Information Extrapolation Using Motion-aligned Auto Regressive Model for Compressed Sensing based Wyner-Ziv Codec

  • Li, Ran;Gan, Zongliang;Cui, Ziguan;Wu, Minghu;Zhu, Xiuchang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.2
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    • pp.366-385
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    • 2013
  • In this paper, we propose a compressed sensing (CS) based Wyner-Ziv (WZ) codec using motion-aligned auto regressive model (MAAR) based side information (SI) extrapolation to improve the compression performance of low-delay distributed video coding (DVC). In the CS based WZ codec, the WZ frame is divided into small blocks and CS measurements of each block are acquired at the encoder, and a specific CS reconstruction algorithm is proposed to correct errors in the SI using CS measurements at the decoder. In order to generate high quality SI, a MAAR model is introduced to improve the inaccurate motion field in auto regressive (AR) model, and the Tikhonov regularization on MAAR coefficients and overlapped block based interpolation are performed to reduce block effects and errors from over-fitting. Simulation experiments show that our proposed CS based WZ codec associated with MAAR based SI generation achieves better results compared to other SI extrapolation methods.