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Underdetermined mixing matrix estimation based on time-frequency single source points detection and eigenvalue decomposition
In this paper, a method of mixing matrix estimation based on time-frequency single source points detection and eigenvalue decomposition is proposed...
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A novel mixing matrix estimation method for underdetermined blind source separation based on sparse subspace clustering
It is essential to accurately estimate the mixing matrix and determine the number of source signals in the problem of underdetermined blind source...
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A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions
Predictive recursion (PR) is a fast, recursive algorithm that gives a smooth estimate of the mixing distribution under the general mixture model....
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Underdetermined mixing matrix estimation based on joint density-based clustering algorithms
In underdetermined blind source separation (UBSS), the estimation of the mixing matrix is crucial because it directly affects the performance of...
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Bayesian variable selection for matrix autoregressive models
A Bayesian method is proposed for variable selection in high-dimensional matrix autoregressive models which reflects and exploits the original matrix...
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Can we realize nonnegative blind source separation with incomplete matrix?
In this paper, we propose an algorithm for nonnegative blind source separation (N-BSS) using incomplete matrix and, moreover, find and prove the...
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SSNet: a joint learning network for semantic segmentation and disparity estimation
Joint learning for semantic segmentation and disparity estimation is adopted to scene parsing for mutual benefit. However, existing joint learning...
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Intelligent identification of concrete uniformity based on dynamic mixing
The uniformity of concrete is an important reference for the maturity of concrete, and is also closely related to the quality and safety of the...
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On Parsimonious Modelling via Matrix-Variate t Mixtures
Mixture models for matrix-variate data have becoming more and more popular in the most recent years. One issue of these models is the potentially...
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A novel mixing matrix estimation algorithm in instantaneous underdetermined blind source separation
Due to the lack of sufficient prior information, how to estimate the mixing matrix in multiple underdetermined blind source separation (UBSS) models...
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Underdetermined mixing matrix estimation based on artificial bee colony optimization and single-source-point detection
It is difficult to solve the problem of underdetermined blind source separation (UBSS) since the mixing system is not invertible. Therefore,...
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EM-Gaze: eye context correlation and metric learning for gaze estimation
In recent years, deep learning techniques have been used to estimate gaze—a significant task in computer vision and human-computer interaction....
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Clustering longitudinal ordinal data via finite mixture of matrix-variate distributions
In social sciences, studies are often based on questionnaires asking participants to express ordered responses several times over a study period. We...
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Learning Channel Importance for High Content Imaging with Interpretable Deep Input Channel Mixing
Uncovering novel drug candidates for treating complex diseases remain one of the most challenging tasks in early discovery research. To tackle this...
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Robust channel estimation based on the maximum entropy principle
Channel estimation (CE) is one of the crucial and fundamental elements of signal processing, especially considering the requirement of high accuracy...
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CMT-6D: a lightweight iterative 6DoF pose estimation network based on cross-modal Transformer
6DoF pose estimation has received much attention in recent years. A key challenge is the difficulty of estimating object pose when the target texture...
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Dual Graph Networks for Pose Estimation in Crowded Scenes
Pose estimation in crowded scenes is key to understanding human behavior in real-life applications. Most existing CNN-based pose estimation methods...
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Density estimation for toroidal data using semiparametric mixtures
Toroidal data is an extension of circular data on a torus and plays a critical part in various scientific fields. This article studies the density...
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Subspace multi-regularized non-negative matrix factorization for hyperspectral unmixing
Hyperspectral unmixing (HU) is an important task in hyperspectral image (HSI) processing, which estimates endmembers and their corresponding...
