Results 31 to 40 of about 35,609 (308)
The Hamiltonian extended Krylov subspace method
The Electronic Journal of Linear Algebra, 2022 An algorithm for constructing a $J$-orthogonal basis of the extended Krylov subspace$\mathcal{K}_{r,s}=\operatorname{range}\{u,Hu, H^2u,$ $ \ldots, $ $H^{2r-1}u, H^{-1}u, H^{-2}u, \ldots, H^{-2s}u\},$where $H \in \mathbb{R}^{2n \times 2n}$ is a large (and sparse) Hamiltonian matrix is derived (for $r = s+1$ or $r=s$).
Peter Benner +2 more
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Adaptive detection of a signal known only to lie on a line in a known subspace, when primary and secondary data are partially homogeneous [PDF]
, 2006 This paper deals with the problem of detecting a signal, known only to lie on a line in a subspace, in the presence of unknown noise, using multiple snapshots in the primary data.
Kraut, Shawn +5 more
core +1 more source
Multiway Filtering Based on Fourth-Order Cumulants
EURASIP Journal on Advances in Signal Processing, 2005 We propose a new multiway filtering based on fourth-order cumulants for the denoising of noisy data tensor with correlated Gaussian noise. The classical multiway filtering is based on the TUCKALS3 algorithm that computes a lower-rank tensor ...
Muti Damien, Bourennane Salah
doaj +1 more source
Extended Averaged Learning Subspace Method for Hyperspectral Data Classification
Sensors, 2009 Averaged learning subspace methods (ALSM) have the advantage of being easily implemented and appear to outperform in classification problems of hyperspectral images.
Yoshifumi Yasuoka +4 more
doaj +1 more source
On data preprocessing for subspace methods
Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2002 In modern data analysis often the first step is to perform some data preprocessing, e.g. detrending or elimination of periodic components of known period length. This is normally done using least squares regression. Only afterwards black box models are estimated using either pseudo-maximum-likelihood methods, prediction error methods or subspace ...
openaire +4 more sources
Comparison of Triply Periodic Minimal Surface Energy Absorbers Under Uniaxial Compressive Loading
Advanced Engineering Materials, EarlyView.This study investigates LCD 3D printed Triply Periodic Minimal Surface (TPMS) structures as mechanical energy absorbers. By comparing various base designs and layered combinations under uniaxial compression, it identifies that a Diamond‐Gyroid sandwich structure offers superior performance.
Sergej Grednev +2 more
wiley +1 more source
Exciton Radiative Lifetimes in Hexagonal Diamond Ge and SixGe1–x Alloys
Advanced Optical Materials, EarlyView.Strong room‐temperature photoluminescence reported in hexagonal Ge conflicts with theory predicting a nearly dark band edge. First‐principles calculations of excitonic radiative lifetimes fill a key gap in this debate, showing that pristine hexagonal Ge remains intrinsically weakly emissive, while Si alloying only modestly shortens the lifetime and ...
Michele Re Fiorentin +2 more
wiley +1 more source
Krylov Subspace Methods in Dynamical Sampling [PDF]
Sampling Theory in Signal and Image Processing, 2016 Let $B$ be an unknown linear evolution process on $\mathbb C^d\simeq l^2(\mathbb Z_d)$ driving an unknown initial state $x$ and producing the states $\{B^\ell x, \ell = 0,1,\ldots\}$ at different time levels. The problem under consideration in this paper is to find as much information as possible about $B$ and $x$ from the measurements $Y=\{x(i)$, $Bx ...
Akram Aldroubi, Ilya A. Krishtal
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Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality [PDF]
, 2004 A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules.
Harris, C. J. +3 more
core +1 more source
Dual subspace discriminative projection learning
, 2021 In this paper, we propose a dual subspace discriminative projection learning (DSDPL) framework for multi-category image classification. Our approach reflects the notion that images are composed of class-shared information, class-specific information, and
Gao, Y, Belous, G, Busch, A
core +1 more source