This paper proposes the use of density-based spatial clustering of application with noise
(DBSCAN) and the Hough transform to estimate the mixing matrix in underdetermined blind …

Studying the effectiveness of certain policies on load management requires detailed
knowledge about the consumption pattern of end-use sectors. The consumption pattern …

Sparse component analysis (SCA) has been widely used for blind source separation (BSS)
for many years. Recently, SCA has been applied to operational modal analysis (OMA) …

For dual‐channel time‐frequency (TF) overlapped signals with low sparsity in
underdetermined blind source separation (UBSS), this paper proposes an effective method …

针对欠定盲源分离混合矩阵的估计问题, 提出一种基于局部方向密度检测的孤立时频点处理与霍
夫变换相结合的混合矩阵估计算法. 首先通过变换域单源时频点处理增强信号的稀疏性 …

The separation of an underdetermined audio mixture can be performed through sparse
component analysis (SCA) that relies however on the strong hypothesis that source signals …

In this paper we present a survey of Blind Signal Separation (BSS) methods based on
independence (Independent Component Analysis) and sparsity (Sparse Component …

The 3D models, represented by vertex positions and the association between triangles and
vertices, colors, normals and texture information, are stored as virtual reality modeling …

In this work, underdetermined blind decomposition method is developed to recognize
individual components from the three-way fluorescent spectra of their mixtures by using …

Data or signal separation is one of the critical areas of data analysis. In this work, the
problem of non-negative data separation is considered. The problem can be briefly …