Results 31 to 40 of about 488 (114)
Clustering with Spectral Norm and the k-Means Algorithm [PDF]
2010 IEEE 51st Annual Symposium on Foundations of Computer Science, 2010 There has been much progress on efficient algorithms for clustering data points generated by a mixture of $k$ probability distributions under the assumption that the means of the distributions are well-separated, i.e., the distance between the means of any two distributions is at least $Ω(k)$ standard deviations.
Amit Kumar 0001, Ravindran Kannan
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Multiple Spectral-Spatial Representation Based on Tensor Decomposition for HSI Anomaly Detection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 To exploit the spectral-spatial information of hyperspectral image (HSI) and achieve higher the detection accuracy, a novel multiple spectral-spatial representation based on tensor decomposition method is proposed for HSI anomaly detection (AD) in this ...
Yujian Wang +5 more
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A Note on Spectrally Dominant Norms
Journal of Algebra, 2000 Let \(A\) be a finite-dimensional associative complex algebra. A vector space norm on it is called stable if there exists a positive constant \(\sigma\) such that \(\|x^n\|\leq\sigma\|x\|^n\) for every \(x\in A\) and all \(n\). It is known that stable norms on \(A\) are spectrally dominant (i.e., for every \(x\in A\), the spectral radius of \(x\leq\|x\|
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On the norms and Hadamard product of Toeplitz matrices involving Leonardo numbers [PDF]
Mathematica MoravicaIn this study, we consider the Toeplitz matrices with entries being Leonardo numbers. We have found upper and lower bounds for the spectral norms of these matrices, considering also the Hadamard product of this type of matrix.
Catarino Paula +4 more
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Improving Generalizability of Spectral Reflectance Reconstruction Using L1-Norm Penalization
Sensors, 2023 Spectral reflectance reconstruction for multispectral images (such as Weiner estimation) may perform sub-optimally when the object being measured has a texture that is not in the training set.
Pengpeng Yao, Hochung Wu, John H. Xin
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A Novel Case of Practical Exponential Observer Using Extended Kalman Filter
IEEE Access, 2018 This technical note presents a case of practical exponential observer using extended Kalman filter (EKF) independent of certain restrictions, such as online check and estimation error of initial state.
Daxiong Ji +10 more
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Zhejiang Daxue xuebao. Lixue ban, 2014 Based on the general theory of matrix and some properties of (k,h)-Fibonacci and (k,h)-Lucas numbers，the upper and lower bounds for the spectral norms of r-circulant matrices and are given.
SHENShouqiang(沈守强) +1 more
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On the Upper Bounds for the Matrix Spectral Norm
CoRRWe consider the problem of estimating the spectral norm of a matrix using only matrix-vector products. We propose a new Counterbalance estimator that provides upper bounds on the norm and derive probabilistic guarantees on its underestimation. Compared to standard approaches such as the power method, the proposed estimator produces significantly ...
Alexey Naumov +3 more
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Spectral norms in spaces of polynomials
Dolomites Research Notes on Approximation, 2022 Summary: We consider a very general case of vector spaces of multivariate polynomials equipped with some norms. Between them we single out a class of spectral norms, that satisfy the condition \(\|P^k \| =\|P\|^k\) for all positive integer \(k\). In spaces of polynomials one can consider some linear operators that are usually unbounded, for example ...
Baran, Mirosław, Kowalska, Agnieszka
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Hyperspectral-Multispectral Image Fusion via Tensor Ring and Subspace Decompositions
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Fusion from a spatially low resolution hyperspectral image (LR-HSI) and a spectrally low resolution multispectral image (MSI) to produce a high spatial-spectral HSI (HR-HSI), known as hyperspectral super resolution, has risen to a preferred topic for ...
Honghui Xu +4 more
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