Convolutive blind source separation method based on tensor decomposition by Baoze MA, Tianqi ZHANG, Zeliang AN, Pan DENG

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Detecting memberships in multiplex networks via nonnegative matrix factorization and tensor decomposition by Fengqin Tang, Xiaozong Wang, Xuejing Zhao, Chunning Wang

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Indoor Wi-Fi fingerprint localization method based on CSI tensor decomposition by Mu ZHOU, Yuexin LONG, Qiaolin PU, Yong WANG, Wei HE

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Blind estimation of spreading codes for multi-antenna LC-DS-CDMA signals based on tensor decomposition by Zhijin ZHAO, Hui YIN, Fangfang QIANG, Junna SHANG

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Channel estimation for double IRS-assisted millimeter wave MIMO systems based on tensor decomposition and manifold optimization by FENG Kaihui, LIU Chen, HUANG Zheng, SONG Yunchao, GAO Runqin

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A review of drug knowledge discovery using BioNLP and tensor or matrix decomposition by Mina Gachloo, Yuxing Wang, Jingbo Xia

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Covid-19 pandemic data analysis using tensor methods by Dipak Dulal, Ramin Goudarzi Karim, Carmeliza Navasca

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Tensor‐based direction of arrival estimation with array virtual translation technique by Guimei Zheng, Jiaqiang Peng, Hongzhen Wang, Yuwei Song

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Multichannel Enhanced Millimeter-Wave SAR Imaging via Low-Rank Tensor-Train Decomposition by Bangjie Zhang, Gang Xu, Xiang-Gen Xia, Jianlai Chen, Rui Zhou, Shuai Shao, Wei Hong

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Low Tensor Rank Constrained Image Inpainting Using a Novel Arrangement Scheme by Shuli Ma, Youchen Fan, Shengliang Fang, Weichao Yang, Li Li

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Tensor-based approach to the co-prime planar array signal processing by Wei RAO, Yufeng GUI, Dan LI

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CUSE-TD Algorithm for Precision Detection of Coherent and Uncorrelated Signals by Rohini Dakulagi, Ravi Raushan, Soham Dutta, Mohammed Theeb Alosaimi, Miguel Villagomez-Galindo

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Detecting Invalid Associations between Fare Machines and Metro Stations Using Smart Card Data by Pengfei Zhang, Zhenliang Ma, Xiaoxiong Weng

“…The tensor decomposition extracts features of passenger flows and travel times passing through fare machines. …”
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Video tamper detection method based on nonnegative tensor factorization by Xue-li ZHANG, Tian-qiang HUANG, Jing LIN, Wei HUANG

“…The authenticity and integrity of video authentication is one of the important contents in information security field.A video tampering detection method based on non-negative tensor decomposition was proposed for video inter-frame tampering.First of all,spectral feature of video frame was extracted quickly.The video was described by a three-dimensional tensor which created by the main compression feature.The tensor was factorized by Tucker non-negative decomposition method and then the time dimension matrix was extracted to calculate correlation.Finally,the tampering position was determined by using the Chebyshev’s inequality.Experiments show that this method can detect the video inter-frame tampering quickly and robustly.…”
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Improved CPD based DOA estimation of nested array by Sibei CHENG, Xiao LUO, Bochou JIANG, Yuting WANG, Huanyu WU

“…In order to avoid searching the peak value in space domain, when estimating nested array’s the direction of direction of arrival(DOA), the canonical polyadic decomposition(CPD) was applied into the nested array, namely using the one time singular value decomposition(SVD), bilinear mapping and tensor decomposition to obtain the steering vector matrix and arrival angle.However, the existing CPD algorithm only can be applied in noiseless environment, the algorithm was improved by utilizing SVD two times, and was made to be applied in both noiseless and noisy environments.The simulation results demonstrate that in the same signal to noise ratio(SNR) and snapshot, the DOA estimation algorithm of nested array based on the improved CPD has better performances and less running time than the MUSIC and space smoothing algorithms.…”
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Low pilot overhead parametric channel estimation scheme for RIS-assisted mmWave MIMO systems by LI Shuangzhi, YANG Ruiqi, GUO Xin, HUANG Sai

“…To address the timely acquisition of channel state information in reconfigurable intelligent surface (RIS)-assisted millimetre wave (mmWave) multiple-input multiple-output (MIMO) systems, a channel estimation scheme based on tensor decomposition was proposed. Firstly, a channel training mechanism with low pilot overhead was designed using a few passive reflection units and constructing a phase shift matrix. …”
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Data-driven prediction of chemically relevant compositions in multi-component systems using tensor embeddings by Hiroyuki Hayashi, Isao Tanaka

“…This study introduces a predictive model designed to forecast complex multi-component oxide compositions, leveraging data derived from simpler pseudo-binary systems. By applying tensor decomposition and machine learning techniques, we transformed pseudo-binary oxide compositions from the Inorganic Crystal Structure Database (ICSD) into tensor representations, capturing key chemical trends such as oxidation states and periodic positions. …”
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Discovering PDEs Corrections from Data Within a Hybrid Modeling Framework by Chady Ghnatios, Francisco Chinesta

“…It is then employed, first, in a full operator representation regularized optimization problem, where sparsity is promoted, leading to a linear programming problem, and then in a tensor decomposition of the operator’s identification procedure. …”
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Robust angle estimation method for noncircular targets in MIMO radar with mutual coupling by Xianpeng WANG, Yuehao GUO, Mengxing HUANG, Chong SHEN, Chunjie CAO, Wenlong FENG

“…A robust angle estimation method for noncircular targets based on unitary tensor decomposition with mutual coupling in multiple-input multiple-output (MIMO) radar was proposed.Firstly,utilizing the banded symmetric Toeplitz structure of the mutual coupling matrix to eliminate the influence of unknown mutual coupling in tensor field.Then a special augmented tensor was constructed to capture the no circularity and its inherent tensor multidimensional structure of noncircular signals.And taking advantage of the centro-Hermitian characteristic of the augmented tensor to transform the sub-tensor into real-values tensor by the unitary transformation.Finally,the signal subspace estimation based on tensor was obtained by taking advantage of the higher-order singular value decomposition (HOSVD) technology,and then the direction-of-departure (DoD) and direction-of-arrival (DoA) estimation was obtained by utilizing the real-values subspace technology.Due to the consideration of both the noncircularity and multidimensional structure,the proposed algorithm has better recognition performance than the existing angle estimation methods.At the same time,the proposed algorithm only requires real-valued operations and has lower computational complexity.Simulation experiments verify the effectiveness and superiority of the proposed algorithm.…”
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