Results 51 to 60 of about 710,592 (303)
Empirical Evaluation of Four Tensor Decomposition Algorithms [PDF]
, 2007 Higher-order tensor decompositions are analogous to the familiar Singular Value Decomposition (SVD), but they transcend the limitations of matrices (second-order tensors).
Turney, Peter, Turney, Peter D.
core +1 more source
Physics Letters BWe present a first study of the scattering process e + e − → π + π − γ beyond next-to-leading order, aimed at providing preliminary insights required for future NNLO predictions for radiative return processes.
Thomas Dave +3 more
doaj +1 more source
L1-Norm Tucker Tensor Decomposition
IEEE Access, 2019 Tucker decomposition is a standard multi-way generalization of Principal-Component Analysis (PCA), appropriate for processing tensor data. Similar to PCA, Tucker decomposition has been shown to be sensitive against faulty data, due to its L2-norm-based ...
Dimitris G. Chachlakis +2 more
doaj +1 more source
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 +5 more
doaj +1 more source
Adaptive Foam 3D Printing of Ultralight and Multifunctional Materials
Advanced Engineering Materials, EarlyView.Adaptive foam 3D printing, enabled by expandable microspheres, imparts cellular structures to thermoplastic and thermosetting polymers, manufactured through a variety of processes including fused filament fabrication, direct ink writing, digital light processing, and inkjet printing.
Nariman Rajabifar, Amir Ameli
wiley +1 more source
Sensors, 2017 This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling.
Yu-Fei Gao +5 more
doaj +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
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
ANLPT: Self-Adaptive and Non-Local Patch-Tensor Model for Infrared Small Target Detection
Remote Sensing, 2023 Infrared small target detection is widely used for early warning, aircraft monitoring, ship monitoring, and so on, which requires the small target and its background to be represented and modeled effectively to achieve their complete separation. Low-rank
Zhao Zhang +3 more
doaj +1 more source
Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy
Advanced Engineering Materials, EarlyView.Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang +6 more
wiley +1 more source