Search Results - "Expectation–maximization algorithm"

Hypersphere Fitting From Noisy Data Using an EM Algorithm by Lesouple, Julien, Pilastre, Barbara, Altmann, Yoann, Tourneret, Jean-Yves

“…This letter studies a new expectation maximization (EM) algorithm to solve the problem of circle, sphere and more generally hypersphere fitting. This algorithm…”
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Phase I risk-adjusted Bernoulli chart in multistage healthcare processes based on the state-space model by Sogandi, Fatemeh, Aminnayeri, Majid, Mohammadpour, Adel, Amiri, Amirhossein

“…Healthcare processes comprise multiple stages in practice. Also, few researchers have addressed Phase I monitoring of healthcare outcomes. Hence, the purpose…”
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Fast EM-like methods for maximum "a posteriori" estimates in emission tomography by De Pierro, A.R., Yamagishi, M.E.B.

“…The maximum-likelihood (ML) approach in emission tomography provides images with superior noise characteristics compared to conventional filtered…”
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Adaptive Wiener filter based on Gaussian mixture distribution model for denoising chest X-ray CT image by Tabuchi, Motohiro, Yamane, Nobumoto, Morikawa, Yoshitaka

“…In recent decades, X-ray CT imaging has become more important as a result of its high-resolution performance. However, it is well known that the X-ray dose is…”
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Remaining useful life re-prediction methodology based on Wiener process: Subsea Christmas tree system as a case study by Cai, Baoping, Fan, Hongyan, Shao, Xiaoyan, Liu, Yonghong, Liu, Guijie, Liu, Zengkai, Ji, Renjie

“…•A remaining useful life re-prediction method based on Wiener process is proposed.•Current and historical data are used for re-prediction model…”
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3D variability analysis: Resolving continuous flexibility and discrete heterogeneity from single particle cryo-EM by Punjani, Ali, Fleet, David J.

“…[Display omitted] •Continuous structural heterogeneity of proteins is often functionally relevant.•Existing single particle cryo-EM reconstruction algorithms…”
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Distributed identification of stable large-scale isomorphic nonlinear networks using partial observations by Li, Chunhui, Yu, Chengpu

“…Distributed parameter identification in large-scale isomorphic nonlinear multi-agent networks encounters challenges due to inherent nonlinear dynamics and…”
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Noise-enhanced convolutional neural networks by Audhkhasi, Kartik, Osoba, Osonde, Kosko, Bart

“…Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds…”
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Sensitivity analysis of treatment effect to unmeasured confounding in observational studies with survival and competing risks outcomes by Huang, Rong, Xu, Ronghui, Dulai, Parambir S.

“…No unmeasured confounding is often assumed in estimating treatment effects in observational data, whether using classical regression models or approaches such…”
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A transformation‐free linear regression for compositional outcomes and predictors by Fiksel, Jacob, Zeger, Scott, Datta, Abhirup

“…Compositional data are common in many fields, both as outcomes and predictor variables. The inventory of models for the case when both the outcome and…”
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Unified Statistical Channel Model for Turbulence-Induced Fading in Underwater Wireless Optical Communication Systems by Zedini, Emna, Oubei, Hassan Makine, Kammoun, Abla, Hamdi, Mounir, Ooi, Boon S., Alouini, Mohamed-Slim

“…A unified statistical model is proposed to characterize turbulence-induced fading in underwater wireless optical communication (UWOC) channels in the presence…”
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Joint Modelling of Longitudinal Measurements and Time‐to‐Event Outcomes With a Cure Fraction Using Functional Principal Component Analysis by Guo, Siyuan, Zhang, Jiajia, Halabi, Susan

“…ABSTRACT In studying the association between clinical measurements and time‐to‐event outcomes within a cure model, utilizing repeated observations rather than…”
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Classification of PolSAR data with the Complex Riesz distribution by Kammoun, Rayhan, Kessentini, Sameh, Zine, Raoudha

“…This article deals with unsupervised classification strategies applied to polarimetric synthetic aperture radar (PolSAR) images. We discuss the performance of…”
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A common random effect induced bivariate gamma degradation process with application to remaining useful life prediction by Song, Kai, Cui, Lirong

“…Due to the complex structures and the multi-functionality of modern products, there are usually two or more performance characteristics which can reflect a…”
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Robust stochastic configuration networks for industrial data modelling with Student’s-t mixture distribution by Yan, Aijun, Guo, Jingcheng, Wang, Dianhui

“…Data collected from industrial sites commonly contains outliers or noise that obey unknown distributions, making it challenging to establish an accurate…”
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Indirect/Direct Learning Coverage Control for Wireless Sensor and Mobile Robot Networks by Liu, Yen-Chen, Lin, Tsen-Chang, Lin, Mu-Tai

“…This article proposes indirect/direct learning control schemes for wireless sensor and mobile robot networks to cover an environment according to the density…”
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Stochastic parameterization identification using ensemble Kalman filtering combined with maximum likelihood methods by Pulido, Manuel, Tandeo, Pierre, Bocquet, Marc, Carrassi, Alberto, Lucini, Magdalena

“…For modelling geophysical systems, large-scale processes are described through a set of coarse-grained dynamical equations while small-scale processes are…”
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Maximum likelihood estimation for discrete latent variable models via evolutionary algorithms by Brusa, Luca, Pennoni, Fulvia, Bartolucci, Francesco

“…We propose an evolutionary optimization method for maximum likelihood and approximate maximum likelihood estimation of discrete latent variable models. The…”
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Valuation of commodity option prices under a regime-switching model with stochastic convenience yield: Model calibration using flower pollination optimization algorithm by Hamdi, A., Aksikas, I., Smaoui, H., Mehrdoust, F., Noorani, I.

“…This research work seeks to construct a model for commodity spot prices by incorporating the concept of stochastic convenience yield within a Markov-switching…”
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Exploring and reconstructing latent domains for multi-source domain adaptation by Liang, Wanjun, Tan, Meijuan, Meng, Xiangyu, Zhang, Chengzhe, Zhou, Jun, Fu, Chilin, Zhang, Xiaolu, Li, Changsheng

“…Multi-Source Domain Adaptation (MSDA) is receiving increased focus as a technique for reliably transferring knowledge from several source domains to a specific…”
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