Effective Lock Detectors Based on Costas Loop Output for SBPSK Mobile Communications by D. Ferramola, T. Casilli, S. Pradella, G. Giunta, D. Orlando

“…Such estimates are obtained through an iterative strategy relying on the Expectation Maximization algorithm. Moreover, when possible, we provide exact statistical characterizations of the considered decision schemes (including the competitors) or, in the other case, suitable approximations that allow for a straightforward performance evaluation. …”
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Transformers deep learning models for missing data imputation: an application of the ReMasker model on a psychometric scale by Monica Casella, Nicola Milano, Pasquale Dolce, Davide Marocco

“…Traditional methods like mean imputation or regression, commonly used to handle missing data, rely upon assumptions that may not hold on psychological data and can lead to distorted results.MethodsThis study aims to evaluate the effectiveness of transformer-based deep learning for missing data imputation, comparing ReMasker, a masking autoencoding transformer model, with conventional imputation techniques (mean and median imputation, Expectation–Maximization algorithm) and machine learning approaches (K-nearest neighbors, MissForest, and an Artificial Neural Network). …”
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Remaining Useful Life Prediction Based on Wear Monitoring with Multi-Attribute GAN Augmentation by Xiaojun Zhu, Yan Pan, Bin Lan, He Wang, Huixin Huang

“…Furthermore, we establish a Wiener-process-based degradation model with time-varying coefficients to capture stochastic wear deterioration patterns. The expectation-maximization algorithm with Bayesian updating is employed for real-time parameter calibration, enabling a dynamic derivation of the probability density functions for RUL estimation. …”
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A Survey Design for a Sensitive Binary Variable Correlated with Another Nonsensitive Binary Variable by Jun-Wu Yu, Yang Lu, Guo-Liang Tian

“…Likelihood-based inferences including maximum likelihood estimates via the expectation-maximization algorithm, asymptotic confidence intervals, and bootstrap confidence intervals of parameters of interest are derived. …”
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Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization by Yukun Liu, Xiaojing Wei, Daming Shi, Dan Xiang, Junliu Zhong, Hai Su

“…In training, the deep learning and expectation-maximization algorithm are used to optimize models. …”
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Population-Level Cell Trajectory Inference Based on Gaussian Distributions by Xiang Chen, Yibing Ma, Yongle Shi, Yuhan Fu, Mengdi Nan, Qing Ren, Jie Gao

“…CPvGTI utilizes a Gaussian mixture model, optimized by the Expectation–Maximization algorithm, to construct new cell populations in the original data space. …”
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Adaptive Energy Management Strategy for Hybrid Electric Vehicles in Dynamic Environments Based on Reinforcement Learning by Shixin Song, Cewei Zhang, Chunyang Qi, Chuanxue Song, Feng Xiao, Liqiang Jin, Fei Teng

“…We developed a memory library for dynamic environments, employed Dirichlet clustering for driving conditions, and incorporated the expectation maximization algorithm for timely model updating to fully absorb prior knowledge. …”
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An automatic generalized Gaussian mixture-based approach for accurate brain tumor segmentation in magnetic resonance imaging analysis by Khalil Ibrahim Lairedj, Zouaoui Chama, Amina Bagdaoui, Samia Larguech, Serge Dzo Mawuefa Afenyiveh, Younes Menni

“…In the present paper, we propose a new automatic approach that combines thresholding and the Generalized Gaussian Mixture Model (GGMM) with the expectation–maximization algorithm for brain tumor segmentation from Magnetic Resonance Imaging (MRI) histogram data. …”
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Multi-source data-driven Bayesian network for risk analysis of maritime accidents in the high sea by Xiaotong Qu, Chengbo Wang, Chengbo Wang, Ruijia Zhao, Mingxing Fang, Mingxing Fang, Mingxing Fang, Xinlian Xie

“…Subsequently, the Expectation-Maximization algorithm is employed for parameter estimation to handle missing data. …”
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Influence of MHC on genetic diversity and testicular expression of linked olfactory receptor genes by Mingue Kang, Byeongyong Ahn, Jae Yeol Shin, Hye-Sun Cho, Jongan Lee, Chankyu Park

“…We observed significantly higher allelic diversity (P < 0.01) in ORs with strong linkage disequilibrium (LD) to SLA compared to those with weak or no LD, and we identified 48 SLA class I-OR haplotypes using the expectation-maximization algorithm. The genetic diversity of SLA-linked ORs was positively correlated with their expression levels in the testis. …”
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Cluster-Based 3-D Channel Modeling for Massive MIMO in Subway Station Environment by Jianzhi Li, Bo Ai, Ruisi He, Mi Yang, Qi Wang, Bei Zhang, Zhangdui Zhong

“…In the hybrid approach, we apply the space-alternating generalized expectation maximization algorithm to estimate the multipath components (MPCs), and use the multipath component distance-based tracking algorithm and the KPowerMeans algorithm for MPCs tracking and clustering. …”
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Generative Simplex Mapping: Non-Linear Endmember Extraction and Spectral Unmixing for Hyperspectral Imagery by John Waczak, David J. Lary

“…Model parameters are determined using a generalized expectation-maximization algorithm, which guarantees non-negativity for extracted endmembers. …”
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Results of trawl counts for juvenile pink salmon in the Bering and Okhotsk Seas in 2024 and prospects for the returns and catch in the Karaginsky subzone and Okhotsk Sea in 2025 by A. A. Somov, E. A. Shevlyakov, A. N. Starovoitov, V. A. Shevlyakov, I. V. Melnikov

“…Abundance in «northern» and «southern» regional complexes of local stocks is estimated for pink salmon in the Okhotsk Sea using cluster analysis with the expectation-maximization algorithm (EM clustering); the «northern» group prevailed with the ratio 64:36 %.…”
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Area extraction and growth monitoring of sugarcane from multi-source remote sensing images under a polarimetric SAR data compensation based on buildings by Yong Hong, Tianjin Xie, Lengkun Luo, Mi Wang, Deren Li, Qing Zhang, Ting Xu

“…On this basis, the newly planted and ratoon sugarcane were further classified by the expectation maximization algorithm based on the compensated SAR image at the seedling stage. …”
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Distribution and Moments of the Idle Period and Interarrival Time in the G/M/1 Queueing System by Felipe A. Cruz-Perez, Sandra Lirio Castellanos-Lopez, Genaro Hernandez-Valdez, Mario Eduardo Rivero-Angeles

“…Additionally, the accuracy of the derived distribution and moments of the idle period when the LN interarrival time is approximated by HE distributions of different orders (using the Expectation-Maximization algorithm) is investigated. Numerical results show a good fit accuracy between idle period distributions obtained under the LN and the m-th order HE interarrival time models. …”
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Genetic susceptibility of human leukocyte antigen alleles in chronic inflammatory demyelinating polyneuropathy in Korean patients by Soonwook Kwon, Jin Myoung Seok, Hye Lim Lee, Yeon Hak Chung, Hyunjin Ju, Mi Young Jeon, Byoung Joon Kim

“…Haplotype frequencies were estimated using the expectation-maximization algorithm. Results The median age of the patients was 58 years, and 12 (44.4%) were female. …”
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Identification of Differentially Expressed Drought-Responsive Genes in Guar [Cyamopsis tetragonoloba (L.) Taub] by Aref Alshameri, Fahad Al-Qurainy, Abdel-Rhman Gaafar, Salim Khan, Mohammad Nadeem, Saleh Alansi, Hassan O. Shaikhaldein, Abdalrhaman M. Salih

“…RNA-Seq via an expectation-maximization algorithm was used to estimate gene abundance. …”
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A clinical predictive score of high liver iron content in metabolic hyperferritinemia: a retrospective cohort pilot study by Mohamed Lotfi Boughzala, Bruno Pereira, Marc Ruivard, Hervé Lobbes

“…A multivariate analysis followed by a 1000 bootstrap replicate analysis with an expectation–maximization algorithm was used to identify the predictive factors of high liver iron content. …”
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Predicting the impact of patient and private provider behavior on diagnostic delay for pulmonary tuberculosis patients in India: A simulation modeling study. by Sarang Deo, Simrita Singh, Neha Jha, Nimalan Arinaminpathy, Puneet Dewan

“…We used an expectation-maximization algorithm to estimate the parameters underlying these behavioral characteristics, with quantitative data encoded from detailed interviews of 76 and 64 pulmonary TB patients in the 2 Indian cities of Mumbai and Patna, respectively, which were conducted between April and August 2014. …”
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Reconstruction of beam parameters and betatron radiation spectra measured with a Compton spectrometer by M. Yadav, M. H. Oruganti, B. Naranjo, S. Zhang, G. Andonian, Y. Zhuang, Ö. Apsimon, C. P. Welsch, J. B. Rosenzweig

“…We also introduce machine learning and the expected maximization algorithm to reconstruct the primary photon spectrum, employing a multilayer neural network for regression analysis of the energy and angle spectra. …”
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