Results 31 to 40 of about 942,483 (302)

Gaussian Mixture Model for Marine Reverberations

Applied Sciences, 2023
Ocean reverberations, a significant interference source in active sonar, arise as a response generated by random scattering at the receiving end, a consequence of randomly distributed clutter or irregular interfaces. Statistical analysis of reverberation
Tongjing Sun, Yabin Wen, Xuegang Zhang, Bing Jia, Mengwei Zhou   +4 more
doaj   +1 more source

Gaussian Mixture Convolution Networks

CoRR, 2022
To be published in ICLR ...
Celarek, Adam, Hermosilla Casajus, Pedro, Kerbl, Bernhard, Ropinski, Timo, Wimmer, Michael   +4 more
openaire   +3 more sources

Hierarchical Gaussian process mixtures for regression [PDF]

, 2005
As a result of their good performance in practice and their desirable analytical properties, Gaussian process regression models are becoming increasingly of interest in statistics, engineering and other fields.
Titterington, D.M., Murray-Smith, R., Shi, J.Q.   +2 more
core   +1 more source

A Fast Incremental Gaussian Mixture Model. [PDF]

PLoS ONE, 2015
This work builds upon previous efforts in online incremental learning, namely the Incremental Gaussian Mixture Network (IGMN). The IGMN is capable of learning from data streams in a single-pass by improving its model after analyzing each data point and ...
Rafael Coimbra Pinto, Paulo Martins Engel   +1 more
doaj   +1 more source

Automatic image equalization and contrast enhancement using Gaussian mixture modeling [PDF]

, 2012
In this paper, we propose an adaptive image equalization algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution, and the intersection points of the ...
Tjahjadi, Tardi, Turgay Celik, Tardi Tjahjadi, Çelik, Turgay   +3 more
core   +1 more source

On the Reversible Jump Markov Chain Monte Carlo (RJMCMC) Algorithm for Extreme Value Mixture Distribution as a Location-Scale Transformation of the Weibull Distribution

Applied Sciences, 2021
Data with a multimodal pattern can be analyzed using a mixture model. In a mixture model, the most important step is the determination of the number of mixture components, because finding the correct number of mixture components will reduce the error of ...
Dwi Rantini, Nur Iriawan, Irhamah
doaj   +1 more source

An Improved Mixture Model of Gaussian Processes and Its Classification Expectation–Maximization Algorithm

Mathematics, 2023
The mixture of experts (ME) model is effective for multimodal data in statistics and machine learning. To treat non-stationary probabilistic regression, the mixture of Gaussian processes (MGP) model has been proposed, but it may not perform well in some ...
Yurong Xie, Di Wu, Zhe Qiang
doaj   +1 more source

Invariances for Gaussian models [PDF]

, 2015
At the heart of a statistical analysis, we are interested in drawing conclusions about random variables and the laws they follow. For this we require a sample, therefore our approach is best described as learning from data.
Adametz, David
core   +1 more source

Particle Gaussian mixture filters-I

Automatica, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dilshad Raihan Akkam Veettil, Suman Chakravorty   +1 more
openaire   +4 more sources

Multi-Modal Filtering for Non-linear Estimation [PDF]

, 2014
16.01.14 KB. Ok to add to spiral, authors retain copyrightMulti-modal densities appear frequently in time series and practical applications. However, they are not well represented by common state estimators, such as the Extended Kalman Filter and the ...
Deisenroth, Marc P, Deisenroth, MP, Peters, Jan, Kamthe, S, Deisenroth, M., Sanket Kamthe, Kamthe, Sanket, Kamthe, S., Jan Peters, Marc Peter Deisenroth, Peters, J., Peters, J   +11 more
core   +2 more sources