Results 11 to 20 of about 613,484 (243)

Modified Freeman−Durden Decomposition and Deorientation Non-Negative Eigenvalue Decomposition for Multi-Look Polarimetric SAR Data

Remote Sensing
Freeman−Durden Decomposition (FDD) and Non-Negative Eigenvalue Decomposition (NNED) are among the most widely used incoherent polarimetric decomposition algorithms for analyzing fully Polarimetric Synthetic Aperture Radar (PolSAR) data, particularly FDD.
Wentao An, Guangming Chen, Yarong Zou, Qian Feng   +3 more
doaj   +2 more sources

Angle of arrival estimation for broadband signals : a comparison [PDF]

, 2013
This paper reviews and compares three different linear algebraic signal subspace techniques for angle of arrival estimation. These include a polynomial matrix approach to multiple signal classification (MUSIC), a parameterised spatial covariance matrix ...
Weiss, Stephan, S. Weiss, J.G. McWhirter, McWhirter, John G., S. Lambotharan, S. Redif, Lambotharan, Sangarapillai, M. Alrmah, Alrmah, Mohamed Abubaker, Redif, Soydan   +9 more
core   +4 more sources

Eigenvalue enclosures and exclosures for non-self-adjoint problems in hydrodynamics [PDF]

, 2010
In this paper we present computer-assisted proofs of a number of results in theoretical fluid dynamics and in quantum mechanics. An algorithm based on interval arithmetic yields provably correct eigenvalue enclosures and exclosures for non-self-adjoint ...
Langer, M., Brown, Brian Malcolm, Brown, B. Malcolm, Wagenhofer, Markus, Langer, Matthias, Wagenhofer, M., Tretter, C., Marletta, Marco, Tretter, Christine, Marletta, M., Tretter, Christiane   +10 more
core   +4 more sources

Abstract robust coarse spaces for systems of PDEs via generalized eigenproblems in the overlaps [PDF]

, 2013
Coarse spaces are instrumental in obtaining scalability for domain decomposition methods for partial differential equations (PDEs). However, it is known that most popular choices of coarse spaces perform rather weakly in the presence of heterogeneities ...
Dolean Maini, Victorita, Hauret, P., Nataf, F., Pechstein, C., Spillane, N., Scheichl, R.   +5 more
core   +4 more sources

Visualization and selection of Dynamic Mode Decomposition components for unsteady flow

Visual Informatics, 2021
Dynamic Mode Decomposition (DMD) is a data-driven and model-free decomposition technique. It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data.
T. Krake, S. Reinhardt, M. Hlawatsch, B. Eberhardt, D. Weiskopf   +4 more
doaj   +1 more source

Generalized Givens Rotations Applied to Complex Joint Eigenvalue Decomposition

ENP Engineering Science Journal, 2021
This paper shows the different ways of using generalized Givens rotations in complex joint eigenvalue decomposition (JEVD) problem. It presents the different schemes of generalized Givens rotation, justifies the introduced approximations and focuses on ...
Ammar Mesloub
doaj   +1 more source

ddEigenLab.jl: Domain-Decomposition Eigenvalue Problem Lab

, 2021
ddEigenLab.jl: Domain-Decomposition Eigenvalue Problem LabThis work was supported by the German Research Foundation (DFG) under project ...
Stamm, Benjamin, Theisen, Lambert
core   +1 more source

Efficient Sandstorm Image Enhancement Using the Normalized Eigenvalue and Adaptive Dark Channel Prior

Technologies, 2021
A sandstorm image has features similar to those of a hazy image with regard to the obtaining process. However, the difference between a sand dust image and a hazy image is the color channel balance.
Ho Sang Lee
doaj   +1 more source

An Approximate Schur Decomposition-Based Spatial Domain Color Image Watermarking Method

IEEE Access, 2019
In this paper, an approximate Schur decomposition-based spatial domain blind color image watermarking method is proposed to protect the copyright of color images, which has low computation complexity similiar to the watermarking technique in the spatial ...
Qingtang Su, Zihan Yuan, Decheng Liu
doaj   +1 more source

Eigenvalue and Generalized Eigenvalue Problems: Tutorial [PDF]

, 2023
This paper is a tutorial for eigenvalue and generalized eigenvalue problems. We first introduce eigenvalue problem, eigen-decomposition (spectral decomposition), and generalized eigenvalue problem.
Ghojogh, Benyamin, Karray, Fakhri, Crowley, Mark   +2 more
core   +1 more source