Results 51 to 60 of about 23,770 (308)

Tensor‐based matched‐field processing applied to the SWellEx‐96 data

Electronics Letters, 2023
This study proposed a matched field source localization method based on tensor decomposition. By considering the advantages of tensors in multidimensional data processing, a three‐dimensional tensor signal model of space‐time‐frequency is constructed ...
Fangwei Zhu, Guangying Zheng, Xiaowei Guo, Fangyong Wang, Shuanping Du, Linlang Bai   +5 more
doaj   +1 more source

Phase Field Failure Modeling: Brittle‐Ductile Dual‐Phase Microstructures under Compressive Loading

Advanced Engineering Materials, EarlyView.
The approach by Amor and the approach by Miehe and Zhang for asymmetric damage behavior in the phase field method for fracture are compared regarding their fitness for microcrack‐based failure modeling. The comparison is performed for the case of a dual‐phase microstructure with a brittle and a ductile constituent.
Jakob Huber, Jan Torgersen, Ewald Werner
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

A Hybrid Norm for Guaranteed Tensor Recovery

Frontiers in Physics, 2022
Benefiting from the superiority of tensor Singular Value Decomposition (t-SVD) in excavating low-rankness in the spectral domain over other tensor decompositions (like Tucker decomposition), t-SVD-based tensor learning has shown promising performance and
Yihao Luo, Andong Wang, Andong Wang, Guoxu Zhou, Guoxu Zhou, Qibin Zhao   +5 more
doaj   +1 more source

Clustering Patients with Tensor Decomposition

CoRR, 2017
In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records. We present a robust and efficient heuristic to face this problem using tensor decomposition. We present the reasons why this approach is preferable for tasks such as clustering patient records, to ...
Ruffini, Matteo, Gavaldà Mestre, Ricard, Limón, Esther   +2 more
openaire   +4 more sources

Karl Popper and the Mechanisms of Hydrogen Embrittlement

Advanced Engineering Materials, EarlyView.
Representation of the beginning of loss of ductility rather than embrittlement. Small concentrations of hydrogen in a diffusible form within iron are well‐established to harm the mechanical integrity of steels. There are theories that attempt to explain the pernicious role of hydrogen.
H. K. D. H. Bhadeshia
wiley   +1 more source

Decomposition of Fundamental Function of Finsler Space & Some Tensors by Lie-Derivative in GBK- 5RFn

Al-Kitab Journal for Pure Sciences
This paper discuses the decomposition of Fundamental Function of Finsler space by Lie-derivative in generalized fifth recurrent Finsler space for Cartan's fourth curvature tensor K_jkh^i in sense of Berwald.
Adel Alqashbri
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

Creep‐Induced Microstructural Evolution in an A2‐B2 Superalloy

Advanced Engineering Materials, EarlyView.
A 27.3Ta‐27.3Mo‐27.3Ti‐8Cr‐10Al (at.%) refractory high‐entropy alloy with precipitation‐strengthened A2‐B2 microstructure was studied by creep tests at 1030°C, which demonstrate a transition in deformation mechanisms in the range of 100–150 MPa applied stress. This is associated with changes in dislocation–precipitate interactions. Relevant deformation
Liu Yang, Aparajita Pramanik, Sandipan Sen, Shubhashis Dixit, Marcel Muench, R. J. Vikram, Daniel Schliephake, Yolita M. Eggeler, Ankur Chauhan, Martin Heilmaier, Alexander Kauffmann   +10 more
wiley   +1 more source

Orthogonal Tensor Recovery Based on Non-Convex Regularization and Rank Estimation

IEEE Access
In this paper, a method for orthogonal tensor recovery based on non-convex regularization and rank estimation (OTRN-RE) is proposed, which aims to accurately recover the low-rank and sparse components of the tensor.
Xixiang Chen, Jingjing Zheng, Li Zhao, Wei Jiang, Xiaoqin Zhang   +4 more
doaj   +1 more source