Results 21 to 30 of about 3,363 (257)

The detection algorithm based on low rank tensor decomposition of large-scale MIMO

open access: yes上海师范大学学报. 自然科学版, 2017
In this paper,we propose an improved Tucker decomposition algorithm.The tensor is decomposed into two dimensions.By using matrix rank reduction and convergence in both Tucker and improved Tucker algorithm,we get an approximate estimation which can ...
Liu Xingyue   +3 more
doaj   +1 more source

Discovering facts with boolean tensor tucker decomposition [PDF]

open access: yesProceedings of the 22nd ACM international conference on Information & Knowledge Management, 2013
Open Information Extraction (Open IE) has gained increasing research interest in recent years. The first step in Open IE is to extract raw subject--predicate--object triples from the data. These raw triples are rarely usable per se, and need additional post-processing.
Dóra Erdös, Pauli Miettinen
openaire   +2 more sources

Coupled Heterogeneous Tucker Decomposition: A Feature Extraction Method for Multisource Fusion and Domain Adaptation Using Multisource Heterogeneous Remote Sensing Data

open access: yesRemote Sensing, 2022
To excavate adequately the rich information contained in multisource remote sensing data, feature extraction as basic yet important research has two typical applications: one of which is to extract complementary information of multisource data to improve
Tong Gao, Hao Chen, Junhong Lu
doaj   +1 more source

On Optimizing Distributed Tucker Decomposition for Dense Tensors [PDF]

open access: yes2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2017
The Tucker decomposition expresses a given tensor as the product of a small core tensor and a set of factor matrices. Apart from providing data compression, the construction is useful in performing analysis such as principal component analysis (PCA)and finds applications in diverse domains such as signal processing, computer vision and text analytics ...
Venkatesan T. Chakaravarthy   +6 more
openaire   +2 more sources

Hyperspectral image, video compression using sparse tucker tensor decomposition

open access: yesIET Image Processing, 2021
Hyperspectral image and videos provide rich spectral information content, which facilitates accurate classification, unmixing, temporal change detection, and so on.
Samiran Das
doaj   +1 more source

A Comparison of Non-negative Tucker Decomposition and Parallel Factor Analysis for Identification and Measurement of Human EEG Rhythms

open access: yesMeasurement Science Review, 2020
Analysis of changes in the brain neural electrical activity measured by the electroencephalogram (EEG) plays a crucial role in the area of brain disorder diagnostics. The elementary latent sources of the brain neural activity can be extracted by a tensor
Rošt’áková Zuzana   +3 more
doaj   +1 more source

A Two-Stage Framework for Directed Hypergraph Link Prediction

open access: yesMathematics, 2022
Hypergraphs, as a special type of graph, can be leveraged to better model relationships among multiple entities. In this article, we focus on the task of hyperlink prediction in directed hypergraphs, which finds a wide spectrum of applications in ...
Guanchen Xiao   +4 more
doaj   +1 more source

Efficient Nonnegative Tucker Decompositions: Algorithms and Uniqueness [PDF]

open access: yesIEEE Transactions on Image Processing, 2015
appears in IEEE Transactions on Image Processing ...
Guoxu Zhou   +3 more
openaire   +3 more sources

Joint range, angle and polarization estimation in polarimetric FDA-MIMO radar based on Tucker tensor decomposition

open access: yesEURASIP Journal on Advances in Signal Processing, 2023
Frequency diverse array multiple-input multiple-output (FDA-MIMO) radar is an emerging technology to offer range-angle-dependent beampattern. Polarimetric FDA-MIMO radar can sense additional polarization information to improve target identification ...
Qi Zhang, Hong Jiang, Yunchang Liu
doaj   +1 more source

On Optimizing Distributed Tucker Decomposition for Sparse Tensors [PDF]

open access: yesProceedings of the 2018 International Conference on Supercomputing, 2018
The Tucker decomposition generalizes the notion of Singular Value Decomposition (SVD) to tensors, the higher dimensional analogues of matrices. We study the problem of constructing the Tucker decomposition of sparse tensors on distributed memory systems via the HOOI procedure, a popular iterative method.
Venkatesan T. Chakaravarthy   +6 more
openaire   +2 more sources

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