张量分解-Block term decomposition (BTD) 2017.06.11去年差不多这个时候,我在本人的博客上发表了三个关于张量分解的博客,从百度统计来看,很多人阅读了这三篇博文。今天,我再介绍一种张量分解-block term decomposition (BTD),下面将分几个部分对BTD进行介绍。
Here, we present the application of a recently introduced technique, called block term decomposition (BTD) to separate EEG tensors into rank- ( L r , L r ,1) terms, allowing to model more variability in the data than what would be possible with CPD. In a simulation study, we ...
It is shown that a block-term decomposition of this tensor provides the necessary information to block-decouple the given function into a set of functions with small input-output dimensionality. The method is validated on a numerical example....
A block term decomposition of third order tensors 讲座论坛 0 2017-07-17 15:30 清水河校区主楼A1-512 (数学学院会议室) 主讲人 Ren-Cang Li 主讲人介绍 Li Rencang现任美国德克萨斯大学惠灵顿分校教授,于1985年在厦门大学计算数学专业本科毕业,1988年中科院计算数学所获得硕士学位,1995年在美国加州大学伯克利分...
This tensor decomposition method is constrained by quasiperiodicity constraints of fetal and maternal ECG signals. Tensor decompositions are more powerful tools than matrix decomposition, due to employing more information for source separation. Tensorizing abdominal signals and using periodicity constraints of...
In this context, a higher-order Block Term Decomposition (BTD) is applied, for the first time in fMRI analysis. Its effectiveness in handling strong instances of noise is demonstrated via extensive simulation results.doi:10.1007/978-3-319-53547-0_1Christos Chatzichristos...
The predominant bilinear methods can all be seen as a kind of tensor-based decomposition operation that contains a key kernel called "core tensor." Current approaches usually focus on reducing the computation complexity by applying low-rank constraint on the core tensor. In this article, we ...
The block term decomposition (BTD) has been recently proposed as a useful tool for noninvasive AA extraction in electrocardiogram (ECG) signals. However, this tensor factorization technique was assessed only in short fixed segments of an AF ECG. To bridge this gap, the present work evaluates ...
In this paper, we focus on the best approximation in the least-squares sense of a higher-order tensor by a block term decomposition. Using variable projection, we express the tensor approximation problem as a minimization of a cost function on a Cartesian product of Stiefel manifolds. We ...
It is shown that a block-term decomposition of this tensor provides the necessary information to block-decouple the given function into a set of functions with small input-output dimensionality. The method is validated on a numerical example....