Results 11 to 20 of about 942,483 (302)
Progressive Gaussian Mixture Reduction [PDF]
, 2008 For estimation and fusion tasks it is inevitable to approximate a Gaussian mixture by one with fewer components to keep the complexity bounded. Appropriate approximations can be typically generated by exploiting the redundancy in the shape description of the original mixture.
Huber, Marco F., Hanebeck, Uwe D.
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Label GM-PHD Filter Based on Threshold Separation Clustering
Sensors, 2021 Gaussian mixture probability hypothesis density (GM-PHD) filtering based on random finite set (RFS) is an effective method to deal with multi-target tracking (MTT).
Kuiwu Wang, Qin Zhang, Xiaolong Hu
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Compressive Gaussian Mixture Estimation [PDF]
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013 When performing a learning task on voluminous data, memory and computational time can become prohibitive. In this chapter, we propose a framework aimed at estimating the parameters of a density mixture on training data in a compressive manner by computing a low-dimensional sketch of the data.
Bourrier, Anthony +2 more
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Classifying Exoplanets with a Gaussian Mixture Model
The Open Journal of Astrophysics, 2018 Recently, Odrzywolek and Rafelski have found three distinct categories of exoplanets, when they are classified based on density. We first carry out a similar classification of exoplanets according to their density using the Gaussian Mixture Model ...
Soham Kulkarni, Shantanu Desai
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Entropy-Based Anomaly Detection for Gaussian Mixture Modeling
Algorithms, 2023 Gaussian mixture modeling is a generative probabilistic model that assumes that the observed data are generated from a mixture of multiple Gaussian distributions. This mixture model provides a flexible approach to model complex distributions that may not
Luca Scrucca
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Statistical modeling of the sea surface in the presence of abnormal waves [PDF]
E3S Web of Conferences, 2023 A wide range of fundamental and applied problems requires a detailed description of the statistics of abnormal sea waves (freak waves or rouge waves). These waves are characterized not only by a change in ener-gy, but also by strong nonlinearity, leading
Zapevalov A., Knyazkov A.
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Analysis of Information-Based Nonparametric Variable Selection Criteria
Entropy, 2020 We consider a nonparametric Generative Tree Model and discuss a problem of selecting active predictors for the response in such scenario. We investigated two popular information-based selection criteria: Conditional Infomax Feature Extraction (CIFE) and ...
Małgorzata Łazęcka, Jan Mielniczuk
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Prediction of operating dynamics in floating-zone crystal growth using Gaussian mixture model
Science and Technology of Advanced Materials: Methods, 2022 We have applied a Gaussian mixture regression to the prediction of operation dynamics in floating zone crystal growth as an example of a materials process.
R. Omae, S. Sumitani, Y. Tosa, S. Harada
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IEEE Access, 2020 Customized production, quality variation of raw materials and other factors make industrial processes work in multiple operating modes. In general, complex industrial processes have strong nonlinearity under each operating mode. In this paper, a Gaussian
Peng Tang +4 more
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Kullback-Leibler approach to Gaussian mixture reduction [PDF]
, 2007 A common problem in multi-target tracking is to approximate a Gaussian mixture by one containing fewer components; similar problems can arise in integrated navigation.
A.R. Runnalls, Runnalls, Andrew R.
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