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检索条件"主题词=Expectation maximization algorithm"
648 条 记 录,以下是441-450 订阅
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Research on Language Recognition algorithms Based on Segment-Level Features and Automatic Identification  6
Research on Language Recognition Algorithms Based on Segment...
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6th International Conference on Artificial Intelligence and Computer Applications, ICAICA 2024
作者: Zu, Le Kang, Yong Gao, Jie He, Shanshan School of General Education Wannan Medical College Wuhu241002 China
Language recognition technology plays a crucial role in automated speech processing within multilingual environments, particularly under the globalized context where the increasing linguistic diversity poses higher de... 详细信息
来源: 评论
Structure-coupled Variational Bayesian Method for Building Layout Reconstruction
Structure-coupled Variational Bayesian Method for Building L...
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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024
作者: Yin, Zixiang Zeng, Xiaolu Yang, Xiaopeng Liao, Jiancheng Gong, Junbo Beijing Institute of Technology Beijing100081 China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing314001 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China
This paper presents a structure-coupled sparse Bayesian learning method for building layout reconstruction using through-the-wall radar. We characterize the azimuth continuity of the wall and two-dimensional extensibi... 详细信息
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Remaining Useful Life Prediction of Railway Balise Based on Wiener Process Under Varying Temperature Conditions  27
Remaining Useful Life Prediction of Railway Balise Based on ...
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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024
作者: Li, Zhengjiao Zhao, Zishuo Liu, Jiang Cai, Baigen Lu, Debiao School of Automation and Intelligence Beijing Jiaotong University Beijing100044 China
The balise transmission system (BTS) plays a vital role in ensuring reliable ground communication of railway traffic. However, due to the natural loss of circuit operation, harsh working environment and high operating... 详细信息
来源: 评论
Adaptive Radar Detection in Compound-Gaussian Environments with Missing Data  2
Adaptive Radar Detection in Compound-Gaussian Environments w...
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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
作者: Hao, Chenchen Rong, Yao Tang, Mengjiao Li, Fan Wang, Xin Yunnan University Yunnan Key Laboratory of Statistical Modeling and Data Analysis Kunming China Civil Aviation Flight University of China Key Laboratory of Flight Techniques and Flight Safety Guanghan China
This paper addresses adaptive radar detection in scenarios with incomplete observations due to measurement errors, sensor failures, or outliers, where the target is embedded in compound Gaussian clutter with unknown c... 详细信息
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Two-Dimensional Off-Grid DOA Estimation Based on Sparse Bayesian Learning  12
Two-Dimensional Off-Grid DOA Estimation Based on Sparse Baye...
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12th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2024
作者: Qin, Jiale Gui, Shuliang Tian, Zengshan Xiao, Ke Tian, Haitao Chongqing University of Posts and Telecommunications Chongqing400065 China Guangdong Institute of Electronic Information Engineering University of Electronic Science and Technology of China dongguan523000 China
In this paper, a two-dimensional off-grid direction of arrival (DOA) estimation strategy based on sparse Bayesian learning (SBL) is proposed for improving the two-dimensional DOA estimation accuracy of millimeter-wave... 详细信息
来源: 评论
Accurate Delayed Source Model for Multi-Frame Full-Rank Spatial Covariance Analysis  18
Accurate Delayed Source Model for Multi-Frame Full-Rank Spat...
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18th International Workshop on Acoustic Signal Enhancement, IWAENC 2024
作者: Furunaga, Shinya Sawada, Hiroshi Ikeshita, Rintaro Nakatani, Tomohiro Makino, Shoji Waseda University 2-7 Hibikino Wakamatsu-ku Kitakyushu Fukuoka808-0135 Japan Ntt Corporation 2-4 Hikaridai Seika-cho Soraku-gun Kyoto619-0237 Japan
Multi-frame Full-rank Spatial Covariance Analysis (mfFCA) is a technique for a blind source separation method and can be applied to reverberant underdetermined conditions where the sources outnumber the microphones an... 详细信息
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Accelerating the convergence of EM-based training algorithms for RBF networks
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6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001
作者: Lázaro, Marcelino Santamaría, Ignacio Pantaleón, Carlos Dpto. Ing. Comunieaciones ETSII v Telecom Universidad de Cantabria Avda Los Castros 39005 Santander Spain
In this paper, we propose a new expectation-maximization (EM) algorithm which speeds up the training of feedforward networks with local activation functions such as the Radial Basis Function (RBF) nctw ork. The core o... 详细信息
来源: 评论
Unsupervised ensemble learning for genome sequencing
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PATTERN RECOGNITION 2022年 129卷
作者: Pages-Zamora, Alba Ochoa, Idoia Cavero, Gonzalo Ruiz Villalvilla-Ornat, Pol Univ Politecn Catalunya BarcelonaTech UPC SPCOM Grp C-Jordi Girona 31 Barcelona 08034 Spain Univ Navarra Tecnun Manuel Lardizabal 13 San Sebastian 20018 Spain Swiss Fed Inst Technol Erdbeobachtung u Fernerkundung HCP G 33-1Leopold Ruzicka Weg 4 CH-8093 Zurich Switzerland
Unsupervised ensemble learning refers to methods devised for a particular task that combine data pro-vided by decision learners taking into account their reliability, which is usually inferred from the data. Here, the... 详细信息
来源: 评论
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
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BMC BIOINFORMATICS 2004年 第1期5卷 201-201页
作者: Najarian, K Zaheri, M Rad, AA Najarian, S Dargahi, J Univ N Carolina Dept Comp Sci Charlotte NC 28223 USA Amirkabir Univ Technol Comp Engn & IT Dept Tehran Iran Concordia Univ CONCAVE Res Ctr Dept Mech & Ind Engn Quebec City PQ Canada
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two experimental conditions. Mixture mode... 详细信息
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Adaptive quantile low-rank matrix factorization
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PATTERN RECOGNITION 2020年 103卷 107310-107310页
作者: Xu, Shuang Zhang, Chun-Xia Zhang, Jiangshe Xi An Jiao Tong Univ Sch Math & Stat Xian 710049 Shaanxi Peoples R China
Low-rank matrix factorization (LRMF) has received much popularity owing to its successful applications in both computer vision and data mining. By assuming noise to come from a Gaussian, Laplace or mixture of Gaussian... 详细信息
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