Results 51 to 60 of about 1,665,186 (233)
A Color Image Watermarking Based on Tensor Analysis
IEEE Access, 2018 Since most of the color image watermarking methods embed the watermark information in each channel or one channel of a color image, the redundant information of the color image cannot be sufficiently utilized, resulting in the poor ability to resist ...
Haiyong Xu +3 more
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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
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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
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Efficient Tensor Decompositions
, 2020 This chapter studies the problem of decomposing a tensor into a sum of constituent rank one tensors. While tensor decompositions are very useful in designing learning algorithms and data analysis, they are NP-hard in the worst-case. We will see how to design efficient algorithms with provable guarantees under mild assumptions, and using beyond worst ...
openaire +2 more sources
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
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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
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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
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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
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Spectral Methods from Tensor Networks
, 2018 A tensor network is a diagram that specifies a way to "multiply" a collection of tensors together to produce another tensor (or matrix). Many existing algorithms for tensor problems (such as tensor decomposition and tensor PCA), although they are not ...
Anandkumar Animashree +2 more
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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 D.
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