Results 31 to 40 of about 174,528 (270)
Oving Eigenvalues and Eigenvectors [PDF]
, 1971 The Office of Naval Research Department Of The Navy Contract No. N 00014-67-A-0305-0010 ; Project No.
Harris, J.F., Robinson, A.R.
core
The Number of Eigenvalues of a Tensor
, 2010 Eigenvectors of tensors, as studied recently in numerical multilinear algebra, correspond to fixed points of self-maps of a projective space. We determine the number of eigenvectors and eigenvalues of a generic tensor, and we show that the number of ...
Bedford +11 more
core +1 more source
Nonlinear Eigenvalue Approach to Differential Riccati Equations for Contraction Analysis [PDF]
, 2016 In this paper, we extend the eigenvalue method of the algebraic Riccati equation to the differential Riccati equation (DRE) in contraction analysis. One of the main results is showing that solutions to the DRE can be expressed as functions of nonlinear ...
Kawano, Yu, Ohtsuka, Toshiyuki
core +3 more sources
Recycling of Thermoplastics with Machine Learning: A Review
Advanced Functional Materials, EarlyView.This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque +5 more
wiley +1 more source
A Globally Convergent MCA Algorithm by Generalized Eigen-Decomposition [PDF]
International Journal of Computational Intelligence Systems, 2011 Minor component analysis (MCA) are used in many applications such as curve and surface fitting, robust beam forming, and blind signal separation. Based on the generalized eigen-decomposition, we present a completely different approach that leads to ...
Jianbin Gao, Mao Ye, Jianping Li, Qi Xia
doaj +1 more source
How can we naturally order and organize graph Laplacian eigenvectors?
, 2018 When attempting to develop wavelet transforms for graphs and networks, some researchers have used graph Laplacian eigenvalues and eigenvectors in place of the frequencies and complex exponentials in the Fourier theory for regular lattices in the ...
Saito, Naoki
core +2 more sources
Nanoplasmonics Reveal Ionic‐Strength‐Driven Hydration of Nanoparticles
Advanced Functional Materials, EarlyView.Localized surface plasmon resonance (LSPR) of gold nanoparticles (AuNPs) is modulated by ionic‐strength‐dependent hydration shell compression. A predictive model connects shell thickness to non‐radiative damping and spectral shifts over seven orders of magnitude.
Yeeun Song +4 more
wiley +1 more source
Estimating Angle of Arrival and Output Signals to Noise Ratio for Wideband Signals [PDF]
Engineering and Technology Journal, 2016 Multiple Signal Classification (MUSIC) algorithm is the most popular algorithm to estimate angle of arrival (AOA) for narrowband signals. This algorithm is based on the use of subspace noise Eigenvectors (Q_n) matrix related to the smallest set of Eigen ...
Bassim Sayed Mohammed
doaj +1 more source
Spectral Convergence of the connection Laplacian from random samples
, 2015 Spectral methods that are based on eigenvectors and eigenvalues of discrete graph Laplacians, such as Diffusion Maps and Laplacian Eigenmaps are often used for manifold learning and non-linear dimensionality reduction.
Singer, Amit, Wu, Hau-tieng
core +1 more source
Computational Modeling of Reticular Materials: The Past, the Present, and the Future
Advanced Materials, EarlyView.Reticular materials are advanced materials with applications in emerging technologies. A thorough understanding of material properties at operating conditions is critical to accelerate the deployment at an industrial scale. Herein, the status of computational modeling of reticular materials is reviewed, supplemented with topical examples highlighting ...
Wim Temmerman +3 more
wiley +1 more source