ESTIMATION METHOD OF LOAD SPECTRUM DISTRIBUTION BASED ON EM ALGORITHM by SU Fang, CHEN XiaoNan, WANG ChenSheng, ZHAO HaiYan

“…Take RF-half shaft torque as the research object,the mixture Gaussian fitting method based on EM was suggested. n Code software was used for rain flow counting and the load cycle was described with the vector S.The cluster number and cluster center loading were got from the clustering of the loading cycle by the SPSS software,and using EM algorithm to resolve the mean and covariance matrix of Gaussian component. …”
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Robust Mean Change-Point Detecting through Laplace Linear Regression Using EM Algorithm by Fengkai Yang

“…By representing the Laplace distribution as an appropriate scale mixture of normal distribution, we developed the expectation maximization (EM) algorithm to estimate the position of mean change-point. …”
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Template attack of Crypto chip based on clustering by Zhen WU, Zhibo DU, Min WANG, Chunling XIANG

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ESTIMATION OF THE SHAPE PARAMETER IN LOMAX DISTRIBUTION BASED ON INTERVAL DATA by LONG Bing, XI ChangXin

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Joint symbol detection and channel estimation for MIMO-OFDM systems via the variational Bayes EM algorithm by ZHANG Xiao-ying, WEI Ji-bo, WANG De-gang, XIONG Chun-lin

“…A new joint symbol detection and channel estimation algorithm was proposed for MIMO-OFDM systems over the time-varying fading channel based on the variational Bayes expectation maximization algorithm and Turbo principle.The channel estimation error covariance matrix was considered in the soft-input soft-output detector which circumvented the undesirable exhaustive search via list sphere decoder（LSD）.In addition,a novel Kalman forward-backward channel estimator was derived based on the posterior distributions of the transmitted symbols which were obtained from the space-time detection.Simulation results show that the proposed algorithm has more robust performance than the conven-tional EM algorithm and decision-directed technique in the time varying multipath channel.…”
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New EM parameter estimation algorithm for a type of micro-motion SFM signal by Yong-yan JIANG, Shi-yuan ZHANG

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RELIABILITY ANALYSIS OF DATA FUSION BASED ON A MIXED BASIS DISTRIBUTION METHOD by ZHANG XiaoJie, TANG JiaYin

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EM-based blind LDPC identification in multipath channels by Yu LIU, Fanggang WANG, Jingwen ZHANG, Bo AI, Zhangdui ZHONG

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POINT ESTIMATION OF THE PARAMETER OF GEOMETRIC DISTRIBUTION UNDER A PARTICULAR RANDOM CENSORING TEST by HE ChaoBing

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Statistical Inferences to the Parameter and Reliability Characteristics of Gamma-mixed Rayleigh Distribution under Progressively Censored Data with Application by Kousik Maiti, Suchandan Kayal

Subjects: “…Expectation-Maximization (EM) algorithm…”
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Robust identification for input non‐uniformly sampled Wiener model by the expectation‐maximisation algorithm by Qibing Jin, Zeyu Wang

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Fitting of nonnegative physical models based on statistical divergence: application to thermally stimulated depolarization currents by Yasunobu Ando, Shusuke Kasamatsu, Suguru Iwasaki, Yumi Tanaka

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Fault Diagnosis and Prediction of Continuous Industrial Processes Based on Hidden Markov Model-Bayesian Network Hybrid Model by Jiarula Yasenjiang, Chenxing Xu, Shengpeng Zhang, Xin Zhang

“…To alleviate this problem, a hidden Markov model-Bayesian network (HMM-BN) hybrid model is proposed to alleviate the local optimum problem in the EM algorithm and diagnose the fault root cause variable. …”
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An Optimal Algorithm for Determining Risk Factors for Complex Diseases: Depressive Disorder, Osteoporosis, and Fracture in Young Patients with Breast Cancer Receiving Curative Surg... by Chieh-Yu Liu, Chun-Hung Chang

“…Second, the expectation-maximization (EM) algorithm is used for clustering the multidimensional coordinates for each category of variable. …”
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Binaural Active Audition for Humanoid Robots to Localise Speech over Entire Azimuth Range by Hyun-Don Kim, Kazunori Komatani, Tetsuya Ogata, Hiroshi G. Okuno

“…The expectation-maximisation (EM) algorithm helped the system to cope with several moving sound sources and reduce localisation errors. …”
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Hybrid Deep-Learning Framework Based on Gaussian Fusion of Multiple Spatiotemporal Networks for Walking Gait Phase Recognition by Tao Zhen, Jian-lei Kong, Lei Yan

“…The framework proposed in this paper implements the inner loop that also contains the EM algorithm in the outer loop and optimizes the reverse gradient in the entire network. …”
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Risk-adaptive access control model for big data in healthcare by Zhen HUI, Hao LI, Min ZHANG, Deng-guo FENG

“…While dealing with the big data in healthcare,it was difficult for a policy maker to foresee what information a doctor may need,even to make an accurate access control policy.To deal with it,a risk-based access control model that regulates doctors’ access rights adaptively was proposed to protect patient privacy.This model analyzed the history of access,applies the EM algorithm and the information entropy technique to quantify the risk of privacy violation.Using the quantified risk,the model can detect and control the over-accessing and exceptional accessing of patients’ data.Experimental results show that this model is effective and more accurate than other models.…”
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GMM-based localization algorithm under NLOS conditions by Wei CUI, Cheng-dong WU, Yun-zhou ZHANG, Zi-xi JIA, Long CHENG

“…Aiming at indoor node localizations of WSN,a node localization algorithm,where priori-knowledge is not necessary,was proposed.on basis of analyzing the error model,combined with Gaussian mixture model (GMM).By training the distance measurements containing NLOS errors,the more accurate range estimations can be obtained.For higher localization accuracy,the particle swarm optimization (PSO) was introduced to optimize the expectation-maximization (EM)algorithm.Finally,by using the residual weighting algorithm to estimate the distance,the estimation coordinates of target nodes can be determined.The proposed algorithm was proved to be effective through simulation experiments.…”
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On the Estimation of k-Regimes Switching of Mixture Autoregressive Model via Weibull Distributional Random Noise by Rasaki, Olawale Olanrewaju, Anthony, Gichuhi Waititu, Nafiu, Lukman Abiodun

“…We developed and established a Weibull Mixture Autoregressive model of k-regimes via WMAR(k; p1, p2, , pk ) with Expectation-Maximization (EM) algorithm adopted as parameter estimation technique. …”
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Fréchet Random Noise for k-Regime-Switching Mixture Autoregressive Model by Rasaki, Olawale Olanrewaju, Anthony, Gichuhi Waititu, Nafiu, Lukman Abiodun

“…Fréchet Mixture Autoregressive (FMAR) model of k-regime-switching, denoted by FMAR(k; p1, p2 ,, pk ) was developed and Expectation-Maximization (EM) algorithm was used as a method of parameter estimation for the embedded coefficients of AR of k-mixing weights and lag pk. …”
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