On the compression of translation operator tensors in FMM-FFT-accelerated SIE simulators via tensor decompositions by Qian, Cheng, Yucel, Abdulkadir C.

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Tensor factorization for missing data imputation in medical questionnaires by Dauwels, Justin, Garg, Lalit, Earnest, Arul, Pang, Leong Khai

“…Measures such as normalized root mean square error, bias and variance are used to assess the performance of the proposed tensor-based methods in comparison with other widely used approaches, such as mean substitution, regression imputations and k-nearest neighbor estimation. …”
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Multi-channel EEG compression based on matrix and tensor decompositions by Srinivasan, K., Dauwels, Justin, Reddy, M. Ramasubba, Cichocki, Andrzej

“…Compression schemes for EEG signals are developed based on matrix and tensor decomposition. Various ways to arrange EEG signals into matrices and tensors are explored, and several matrix and tensor decomposition schemes are applied, including SVD, CUR, PARAFAC, the Tucker decomposition, and recent random fiber selection approaches. …”
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A survey on applications of semi-tensor product method in engineering by Li, Haitao, Zhao, Guodong, Meng, Min, Feng, June

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Tensor decomposition based R-dimensional matrix pencil method by Wen, Fuxi, Tay, Wee Peng

“…Furthermore, it is straightforward to extend the proposed R-D tensor MP to other MP type methods, such as R-D unitary tensor MP, R-D beamspace tensor MP.…”
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Tensor decomposition for spatial-temporal traffic flow prediction with sparse data by Yang, Funing, Liu, Guoliang, Huang, Liping, Chin, Cheng Siong

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Towards a polynomial algorithm for optimal contraction sequence of tensor networks from trees by Xu, Jianyu, Liang, Ling, Deng, Lei, Wen, Changyun, Xie, Yuan, Li, Guoqi

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A highly-parallel and energy-efficient 3D multi-layer CMOS-RRAM accelerator for tensorized neural network by Huang, Hantao, Ni, Leibin, Wang, Kanwen, Wang, Yuangang, Yu, Hao

Subjects: “…Tensorized Neural Network (TNN)…”
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Robust angle estimation for MIMO radar with the coexistence of mutual coupling and colored noise by Wang, Junxiang, Wang, Xianpeng, Xu, Dingjie, Bi, Guoan

“…This paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. …”
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Multi-channel EEG compression based on 3D decompositions by Srinivasan, K., Dauwels, Justin, Reddy, M. Ramasubba, Cichocki, Andrzej

“…The multi-channel EEG is represented as a three-way tensor (or 3D volume) to exploit both spatial and temporal correlations efficiently. …”
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Latte: cross-framework Python package for evaluation of latent-based generative models by Watcharasupat, Karn N., Lee, Junyoung, Lerch, Alexander

“…Latte (for LATent Tensor Evaluation) is a Python library for evaluation of latent-based generative models in the fields of disentanglement learning and controllable generation. …”
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Synthesis of minimally restrictive optimal stability-enforcing supervisors for nondeterministic discrete event systems by Han, Xiaoguang, Chen, Zengqiang, Su, Rong

“…First, the dynamics of a discrete event system (DES) are converted into an algebraic equation in the framework of Boolean semi-tensor product. Using it, several necessary and sufficient conditions are presented to verify whether a DES is stable or not. …”
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Controllability of Markovian jump Boolean control networks by Meng, Min, Xiao, Gaoxi, Zhai, Chao, Li, Guoqi

“…In this paper, controllability of Markovian jump Boolean control networks (MJBCNs) is studied via semi-tensor product of matrices. First, based on the algebraic expression of the considered Boolean control networks, a necessary and sufficient condition for controllability is presented by iteration equations, which however may lead to high-dimensional matrices. …”
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Surface waves propagating on grounded anisotropic dielectric slab by Chen, Zhuozhu, Shen, Zhongxiang

“…In addition, the propagation characteristics of two hybrid modes supported by the grounded anisotropic slab are analyzed in terms of the slab thickness, slab width, as well as the relative permittivity tensor of the anisotropic slab. Furthermore, different methods are employed to compare the analyses, as well as to validate our derivations. …”
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Multichannel EEG compression : wavelet-based image and volumetric coding approach by Srinivasan, K., Dauwels, Justin, Reddy, M. Ramasubba

“…In particular, multichannel EEG is represented either in the form of image (matrix) or volumetric data (tensor), next a wavelet transform is applied to those EEG representations. …”
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Hyperbolic metamaterials based on quantum-dot plasmon-resonator nanocomposites by Zhukovsky, S. V., Ozel, T., Mutlugun, E., Gaponik, N., Eychmuller, A., Lavrinenko, A. V., Demir, H. V., Gaponenko, S. V.

“…Depending on the thickness of the spacer between the quantum dot and nanoparticle layers, the effective permittivity tensor of the nanocomposite is shown to become indefinite, resulting in increased photonic density of states and strong enhancement of quantum dot luminescence. …”
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Suppressing decoherence in quantum plasmonic systems by the spectral-hole-burning effect by You, Jia-Bin, Xiong, Xiao, Bai, Ping, Zhou, Zhang-Kai, Yang, Wan-Li, Png, Ching Eng, Kwek, Leong Chuan, Wu, Lin

“…Based on our quantum simulations via a quantum tensor network algorithm, we numerically demonstrate the mitigation of this restrictive drawback by hybridizing a plasmonic nanocavity with an emitter ensemble with inhomogeneously-broadened transition frequencies. …”
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Parkinson's disease diagnosis via joint learning from multiple modalities and relations by Lei, Haijun, Huang, Zhongwei, Zhou, Feng, Elazab, Ahmed, Tan, Ee-Leng, Li, Hancong, Qin, Jing, Lei, Baiying

“…In this paper, we propose a joint regression and classification framework for PD diagnosis via magnetic resonance and diffusion tensor imaging data. Specifically, we devise a unified multitask feature selection model to explore multiple relationships among features, samples, and clinical scores. …”
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Nonlocal structured sparsity regularization modeling for hyperspectral image denoising by Zha, Zhiyuan, Wen, Bihan, Yuan, Xin, Zhang, Jiachao, Zhou, Jiantao, Lu, Yilong, Zhu, Ce

“…The nonlocal-based model for hyperspectral image (HSI) denoising first uses nonlocal self-similarity (NSS) prior to group similar full-band patches into 3-D nonlocal full-band groups (tensors) using a block matching (BM) operation, and then a low-rank (LR) penalty is typically applied to each nonlocal full-band group to reduce noise. …”
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Extreme polarization anisotropy in resonant third-harmonic generation from aligned carbon nanotube films by Zhu, Song, Li, Wenkai, Yu, Shengjie, Komatsu, Natsumi, Baydin, Andrey, Wang, Fakun, Sun, Fangyuan, Wang, Chongwu, Chen, Wenduo, Tan, Chuan Seng, Liang, Houkun, Yomogida, Yohei, Yanagi, Kazuhiro, Kono, Junichiro, Wang, Qi Jie

“…Further, through systematic polarization-dependent THG measurements, the values of all elements of the susceptibility tensor are determined, verifying the macroscopically 1D nature of the films. …”
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