Suchergebnisse - expectation–maximization algorithm (EM-algorithm)

An Asymmetric Distribution with Heavy Tails and Its Expectation–Maximization (EM) Algorithm Implementation von Olmos, Neveka M., Venegas, Osvaldo, Gómez, Yolanda M., Iriarte, Yuri A.

“… We developed the expectation–maximization algorithm and present a simulation study. We calculated the moment and maximum likelihood estimators and present three …”
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Dynamic Probabilistic Predictable Feature Analysis for Multivariate Temporal Process Monitoring von Fan, Wei, Zhu, Qinqin, Ren, Shaojun, Zhang, Liang, Si, Fengqi

“… The model parameters are estimated with an efficient expectation-maximization algorithm, where the genetic algorithm and the Kalman filter are designed and incorporated …”
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Identification of Slow-Rate Integrated Measurement Systems Using Expectation-Maximization Algorithm von Kheirandish, Amid, Fatehi, Alireza, Gheibi, Mir Sajjad

“… By selecting finite impulse response (FIR) and autoregressive exogenous (ARX) models for the systems, parameters of them will be accurately estimated in the framework of the expectation-maximization (EM) algorithm …”
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EMORe: motion-robust XD-CMR reconstruction using expectation-maximization (EM) algorithm von Arshad, Syed Murtaza, Potter, Lee C., Lei, Xuan, Ahmad, Rizwan

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A Block EM Algorithm for Multivariate Skew Normal and Skew t -Mixture Models von Lee, Sharon X., Leemaqz, Kaleb L., McLachlan, Geoffrey J.

“… However, parameter estimation via the Expectation-Maximization (EM) algorithm can become very time consuming due to the complicated expressions involved in the E-step that are numerically expensive to evaluate …”
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Offline and Online Parameter Learning for Switching Multirate Processes With Varying Delays and Integrated Measurements von Salehi, Yousef, Huang, Biao

“… varying sampling intervals. First, under the framework of the expectation-maximization (EM) algorithm, offline parameter estimation problem of dual-rate switching augmented regression models is handled …”
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Degradation Modeling Using Stochastic Processes With Random Initial Degradation von Shen, Lijuan, Wang, Yudong, Zhai, Qingqing, Tang, Yincai

“… In degradation tests, it is common to see that the initial degradation levels of test units are heterogeneous. Moreover, the degradation rate of a path may …”
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ANFIS-EM approach for PET brain image reconstruction von Thiyagarajan, Arunprasath, Murugan, Pallikonda Rajasekaran, Subramanian, Kannan

“… expectation maximization algorithm (ANFIS‐EM). This expectation maximization (EM) algorithm provides better image quality when compared with other traditional methodologies …”
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A Generalized Model for Robust Tensor Factorization With Noise Modeling by Mixture of Gaussians von Chen, Xi'ai, Han, Zhi, Wang, Yao, Zhao, Qian, Meng, Deyu, Lin, Lin, Tang, Yandong

“… The low-rank tensor factorization (LRTF) technique has received increasing attention in many computer vision applications. Compared with the traditional matrix …”
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Robust Identification of Nonlinear Systems With Missing Observations: The Case of State-Space Model Structure von Yang, Xianqiang, Liu, Xin, Yin, Shen

“… This paper investigates the robust identification of nonlinear systems in state-space setting with output measurements contaminated with outliers and part of …”
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Indirect/Direct Learning Coverage Control for Wireless Sensor and Mobile Robot Networks von Liu, Yen-Chen, Lin, Tsen-Chang, Lin, Mu-Tai

“… To improve the density function estimation, this study employs an expectation-maximization algorithm and log-likelihood, which maximizes the similarity between the proposed normalized density …”
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The spike‐and‐slab quantile LASSO for robust variable selection in cancer genomics studies von Liu, Yuwen, Ren, Jie, Ma, Shuangge, Wu, Cen

“… Data irregularity in cancer genomics studies has been widely observed in the form of outliers and heavy‐tailed distributions in the complex traits. In the past …”
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Robust SCN for Data-Driven Modeling Based on Heavy-Tailed Noise Distribution von Liu, Xin, Liu, Xiaoqing, Dai, Wei

“… with the stochastic configuration algorithm, which means the hidden nodes number, the input weights, and biases of the SCN learner model …”
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A Theoretical Framework for Change Detection Based on a Compound Multiclass Statistical Model of the Difference Image von Zanetti, Massimo, Bruzzone, Lorenzo

“… The change detection (CD) problem is very important in the remote sensing domain. The advent of a new generation of multispectral (MS) sensors has given rise …”
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A Novel Robust Gaussian Approximate Smoother Based on EM for Cooperative Localization With Sensor Fault and Outliers von Xu, Bo, Guo, Yu, Wang, Lianzhao, Zhang, Jiao

“… In this article, a novel robust Gaussian approximation smoother based on expectation-maximization (EM …”
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Adaptive Radar Detection in the Presence of Missing-data von Aubry, Augusto, Carotenuto, Vincenzo, De Maio, Antonio, Rosamilia, Massimo, Marano, Stefano

“… This article deals with the problem of adaptive radar detection in a missing-data context, where the complete observations (i.e., downstream information loss …”
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Variable-Bit-Rate Video Frame-Size Prediction by the Extended Kalman Filter Using Levenberg-Marquardt Algorithm von Chang, Shih Yu, Wu, Hsiao-Chun, Yan, Kun

“… (in the absence of uncertainty) which is surely not realistic in practice. In this work, we propose a new expectation-maximization (EM …”
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penalized EM algorithm incorporating missing data mechanism for Gaussian parameter estimation von Chen, Lin S, Prentice, Ross L, Wang, Pei

“… The performance of the resulting “penalized EM algorithm incorporating missing data mechanism (PEMM)” estimation procedure is evaluated in simulation studies and in a proteomic data illustration …”
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Robust Degradation Analysis With Non-Gaussian Measurement Errors von Zhai, Qingqing, Ye, Zhi-Sheng

“… Degradation analysis is an effective way to infer the health status and lifetime of products. Due to variability in the measurement, degradation observations …”
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A Competing Risks Model With Multiply Censored Reliability Data Under Multivariate Weibull Distributions von Fan, Tsai-Hung, Wang, Yi-Fu, Ju, She-Kai

“… A competing risks model is composed of more than one failure mode that naturally arises when reliability systems are made of two or more components. A series …”
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