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Video segmentation using multiple features based on em algorithm

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Journal of Systems Engineering and Electronics 2004年第4期15卷 656-662页

作者： ZhangFengchao YangJie LiuErqi InstituteofImageProcessingandPatternRecognition ShanghaiJiaotongUniversityShanghai200030P.R.China TheSecondAcademy ChinaAerospaceofScienceandIndustryCorporationBeijing100854P.R.China

Object-based video segmentation is an important issue for many multimedia applications. A video segmentation method based on em algorithm is proposed. We consider video segmentation as an unsupervised classification problem and apply em algorithm to obtain the maximum-likelihood estimation of the Gaussian model parameters for model-based segmentation. We simultaneously combine multiple features (motion, color) within a maximum likelihood framework to obtain accurate segment results. We also use the temporal consistency among video frames to improve the speed of em algorithm. Experimental results on typical MPEG-4 sequences and real scene sequences show that our method has an attractive accuracy and robustness.

关键词： em algorithm maximum-likelihood estimation video object segmentation

Acceleration of the em algorithm Using the Vector Aitken Method and Its Steffensen Form

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Acta Mathematicae Applicatae Sinica 2017年第1期33卷 175-182页

作者： Xu GUO Qiu-yue LI Wang-li XU School of Statistics Beijing Normal University College of Science China Agricultural University Center for Applied Statistics School of StatisticsRenmin University of China

Based on Vector Aitken （VA） method, we propose an acceleration Expectation-Maximization （em） algorithm, VA-accelerated em algorithm, whose convergence speed is faster than that of em algorithm. The VA-accelerated em algorithm does not use the information matrix but only uses the sequence of estimates obtained from iterations of the em algorithm, thus it keeps the flexibility and simplicity of the em algorithm. Considering Steffensen iterative process, we have also given the Steffensen form of the VA-accelerated em algorithm. It can be proved that the reform process is quadratic convergence. Numerical analysis illustrate the proposed methods are efficient and faster than em algorithm.

关键词： em algorithm VA-accelerated em algorithm convergence rate Steffensen iterative

Robust maximum-likelihood parameter estimation of stochastic state-space systems based on em algorithm

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Progress in Natural Science:Materials International 2007年第9期17卷 1095-1103页

作者： Zhong Lusheng(National Laboratory of Industrial Control Technology,Institute of Industrial Process Control,Zhejiang University,Hangzhou 310027,China) National Laboratory of Industrial Control Technology Institute of Industrial Process Control Zhejiang University Hangzhou 310027 China

This paper addresses the problems of parameter estimation of multivariable stationary stochastic systems on the basis of observed output *** main contribution is to employ the expectation-maximisation(em)method as a means for computation of the maximum-likelihood(ML)parameter estimation of the *** form of the expectation of the studied system subjected to Gaussian distribution noise is derived and parameter choice that maximizes the expectation is also *** results in an iterative algorithm for parameter estimation and the robust algorithm implementation based on technique of QR-factorization and Cholesky factorization is also ***,algorithmic properties such as non-decreasing likelihood value,necessary and sufficient conditions for the algorithm to arrive at a local stationary parameter,the convergence rate and the factors affecting the convergence rate are *** study shows that the proposed algorithm has attractive properties such as numerical stability,and avoidance of difficult initial conditions.

关键词： parameter estimation system identification maximum likelihood(ML) stochastic state-space system em algorithm

Identification of switched nonlinear systems based on em algorithm

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Identification of switched nonlinear systems based on EM alg...

Performance Analysis of em-Based Iterative SNR Estimation for Coded Signals

第三十九届中国控制会议

作者： Chai Xiujun Wang Hongwei Wang Lin Xiao Zhengqing School of Electrical Engineering Xinjiang University School of Control Science and Engineering Dalian University of Technology School of Mathematics and System Sciences Xinjiang University

This study aims to determine how to deal with the identification of switched nonlinear systems（SNSs） with multiple Hammerstein *** identification tasks of SNSs are model detection（MD） and parameters identification（PI）.At the stage of MD,Expectation-Maximization（em） algorithm is used to confirm the switched time and the dwell time of *** the stage of PI,the weighted multi-innovation least square（WMILS） algorithm is proposed to obtain the final parameter estimates for each ***,the effectiveness of the proposed methods is verified through simulation example.

关键词： switched nonlinear systems em algorithm weighed multi-innovation least squares key-term separation principle Hammerstein models

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Performance Analysis of EM-Based Iterative SNR Estimation fo...

Color and direction-invariant nonlocal self-similarity prior and its application to color image denoising

2012 IEEE 11th International Conference on Signal Processing(ICSP 2012)

作者： KE Jing XU Hua WANG Ai-fen Information and Navigation Institute Air Force Engineering University

ISBN: (纸本)9781467321969

This paper considers signal-to-noise ratio （SNR） estimation in transmission systems with an iteratively decodable low-density parity-check （LDPC） code by means of the expectation-maximization （em） algorithm. We present a simplified version of the code-aided （CA） estimation algorithm by introducing the embedded estimation technique to reduce the computational complexity related to the iterative process of the estimator. And we also show that the conventional non-data-aided （NDA） estimators can be interpreted as a special case of the CA estimator. Computer simulations show that the improve CA approach can achieve good estimates at low SNR with significantly less computation.

关键词： SNR estimation iterative LDPC decoding em algorithm

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Science China(Information Sciences) 2020年第12期63卷 87-103页

作者： Qi XIE Qian ZHAO Zongben XU Deyu MENG School of Mathematics and Statistics Xi'an Jiaotong University Macau Institute of Systems Engineering Macau University of Science and Technology

Nonlocal self-similarity(NSS) is one of the most commonly used priors in computer vision and image processing. It aims to make use of the fact that a natural image often possesses many repetitive local patterns, and thus a local image patch always has many similar patches across the image. Through compensatively integrating these similar image patches, their insightful patterns hiding under corrupted noises can be intrinsically extracted. However, for using this prior knowledge, current methods search the similar patches by using simple block matching strategy with Euclidean distance, which largely ignores those patches containing similar local patterns but with different texture-directions and colors. To more sufficiently explore similar patches over an image, in this paper, we propose two new representations for image patches, which facilitate an easy NSS prior for measuring direction-invariant and color-invariant nonlocal selfsimilarity possessed by image patches. Specifically, based on this prior term, we formulate the color image denoising problem as a concise Bayesian posterior estimation framework, and design an efficient expectationmaximization(em) algorithm to solve it. A series of experiments implemented on simulated and real noisy color images demonstrate the superiority of the proposed method as compared with the state-of-the-arts both visually and quantitatively, verifying the potential usefulness of this new NSS prior.

关键词： color image denoising nonlocal self-similarity Gaussian mixture model maximum a posterior (MAP) model em algorithm

Remaining useful life estimation based on Wiener degradation processes with random failure threshold

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Journal of Central South University 2016年第9期23卷 2230-2241页

作者： TANG Sheng-jin YU Chuan-qiang FENG Yong-bao XIE Jian GAO Qin-he SI Xiao-sheng High-Tech Institute of Xi＇an Xi＇an 710025 China

Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold(RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization(em) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.

关键词： condition based maintenance remaining useful life wiener process random failure threshold bayesian em algorithm

Find truth in the hands of the few:acquiring specific knowledge with crowdsourcing

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Frontiers of Computer Science 2021年第4期15卷 5-16页

作者： Tao HAN Hailong SUN Yangqiu SONG Yili FANG Xudong LIU SKLSDE Lab School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100191China Department of Computer Science and Engineering Hong Kong University of Science and TechnologyClearwater BayHong Kong 999077China School of Computer and Information Engineering Zhejiang Gongshang UniversityHangzhou 310018China

Crowdsourcing has been a helpful mechanism to leverage human intelligence to acquire useful ***,when we aggregate the crowd knowledge based on the currently developed voting algorithms,it often results in common knowledge that may not be *** this paper,we consider the problem of collecting specific knowledge via *** the help of using external knowledge base such as WordNet,we incorporate the semantic relations between the alternative answers into a probabilisticmodel to determine which answer is more *** formulate the probabilistic model considering both worker’s ability and task’s difficulty from the basic assumption,and solve it by the expectation-maximization(em)*** increase algorithm compatibility,we also refine our method into semi-supervised *** results show that our approach is robust with hyper-parameters and achieves better improvement thanmajority voting and other algorithms when more specific answers are expected,especially for sparse data.

关键词： crowdsourcing knowledge acquisition em algorithm label aggregation

Regression Analysis of Misclassified Current Status Data with Informative Observation Times

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Journal of Systems Science & Complexity 2023年第3期36卷 1250-1264页

作者： WANG Wenshan XU Da ZHAO Shishun SUN Jianguo Center for Applied Statistical Research School of MathematicsJilin UniversityChangchun 130012China Key Laboratory of Applied Statistics of MOE and School of Mathematics and Statistics Northeast Normal UniversityChangchun 130024China Department of Statistics University of MissouriColumbiaMO 65211USA

Misclassified current status data arises if each study subject can only be observed once and the observation status is determined by a diagnostic test with imperfect sensitivity and *** the situation,another issue that may occur is that the observation time may be correlated with the interested failure time,which is often referred to as informative censoring or observation *** is well-known that in the presence of informative censoring,the analysis that ignores it could yield biased or even misleading *** this paper,the authors consider such data and propose a frailty-based inference *** particular,an em algorithm based on Poisson latent variables is developed and the asymptotic properties of the resulting estimators are *** numerical results show that the proposed method works well in practice and an application to a set of real data is provided.

关键词： Current status data em algorithm informative censoring misclassification proportional hazard model