Results 51 to 60 of about 234,207 (337)
TENSOR MODELING BASED FOR AIRBORNE LiDAR DATA CLASSIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Feature selection and description is a key factor in classification of Earth observation data. In this paper a classification method based on tensor decomposition is proposed.
N. Li +6 more
doaj +1 more source
Randomized Tensor Ring Decomposition and Its Application to Large-scale Data Reconstruction
, 2019 Dimensionality reduction is an essential technique for multi-way large-scale data, i.e., tensor. Tensor ring (TR) decomposition has become popular due to its high representation ability and flexibility.
Cao, Jianting +3 more
core +1 more source
A constructive arbitrary-degree Kronecker product decomposition of tensors [PDF]
, 2016 We propose the tensor Kronecker product singular value decomposition~(TKPSVD) that decomposes a real $k$-way tensor $\mathcal{A}$ into a linear combination of tensor Kronecker products with an arbitrary number of $d$ factors $\mathcal{A} = \sum_{j=1}^R ...
Batselier, Kim, Wong, Ngai
core +2 more sources
Hankel Tensor Decompositions and Ranks [PDF]
SIAM Journal on Matrix Analysis and Applications, 2019 Hankel tensors are generalizations of Hankel matrices. This article studies the relations among various ranks of Hankel tensors. We give an algorithm that can compute the Vandermonde ranks and decompositions for all Hankel tensors. For a generic $n$-dimensional Hankel tensor of even order or order three, we prove that the the cp rank, symmetric rank ...
Jiawang Nie, Ke Ye
openaire +3 more sources
Advanced Engineering Materials, EarlyView.This study reports lightweight polyetherimide triply periodic minimal surfaces lattices coated with carbon nanotube‐reinforced epoxy that combine mechanical robustness with self‐sensing. The conformal coating enhances stiffness, strength and energy absorption while enabling reliable strain monitoring.
A. Triay +3 more
wiley +1 more source
Orthogonal random projection for tensor completion
IET Computer Vision, 2020 The low‐rank tensor completion problem, which aims to recover the missing data from partially observable data. However, most of the existing tensor completion algorithms based on Tucker decomposition cannot avoid using singular value decomposition (SVD ...
Yali Feng, Guoxu Zhou
doaj +1 more source
Portfolio strategy based on nonnegative tensor decomposition
Nantong Daxue xuebao. Ziran kexue ban, 2023 Effective extraction of the inter dependence between the stock pairs from stock price time series can improve the return rate of portfolio investment. This study uses non-negative tensor decomposition technology based on block coordinate descent method ...
XU Xiangjian; MA Haiyang; ZHAO Weihua
doaj +1 more source
SamBaTen: Sampling-based Batch Incremental Tensor Decomposition
, 2017 Tensor decompositions are invaluable tools in analyzing multimodal datasets. In many real-world scenarios, such datasets are far from being static, to the contrary they tend to grow over time.
Gujral, Ekta +2 more
core +1 more source
Decomposing Overcomplete 3rd Order Tensors using Sum-of-Squares Algorithms [PDF]
, 2015 Tensor rank and low-rank tensor decompositions have many applications in learning and complexity theory. Most known algorithms use unfoldings of tensors and can only handle rank up to $n^{\lfloor p/2 \rfloor}$ for a $p$-th order tensor in $\mathbb{R}^{n ...
Ge, Rong, Ma, Tengyu
core +2 more sources
Surface Tension Measurement of Ti‐6Al‐4V by Falling Droplet Method in Oxygen‐Free Atmosphere
Advanced Engineering Materials, EarlyView.In this article, the temperature‐dependent surface tension of free falling, oscillating Ti‐6Al‐4V droplets is investigated in both argon and monosilane doped, oxygen‐free atmosphere. Droplet temperature and oscillation are captured with one single high‐speed camera, and the surface tension is calculated with Rayleigh's formula.
Johannes May +9 more
wiley +1 more source