Results 281 to 290 of about 197,057 (337)
PHLOWER leverages single-cell multimodal data to infer complex, multi-branching cell differentiation trajectories. [PDF]
Nat MethodsCheng M +11 more
europepmc +1 more source
Response of a General Restricted Open-Shell Hartree-Fock Wave Function. I: Formalism, Analytic Gradients, and Electric and Magnetic Response Properties. [PDF]
J Phys Chem ANeese F.
europepmc +1 more source
Exploring Phylogenetic Signal in Multivariate Phenotypes by Maximizing Blomberg's K. [PDF]
Syst BiolMitteroecker P, Collyer ML, Adams DC.
europepmc +1 more source
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2017
This chapter begins with the basic theory of eigenvalues and eigenvectors of matrices. Essential concepts such as characteristic polynomials, the Fundamental Theorem of Algebra, the Gerschgorin circle theorem, invariant subspaces, change of basis, spectral radius and the distance between subspaces are developed.
Ravi P. Agarwal, Cristina Flaut
semanticscholar +6 more sources
This chapter begins with the basic theory of eigenvalues and eigenvectors of matrices. Essential concepts such as characteristic polynomials, the Fundamental Theorem of Algebra, the Gerschgorin circle theorem, invariant subspaces, change of basis, spectral radius and the distance between subspaces are developed.
Ravi P. Agarwal, Cristina Flaut
semanticscholar +6 more sources
Numerical Methods, 2019
In this chapter we present the main results regarding eigenvalues and eigenvectors of compact and/or symmetric operators. This includes the Hilbert–Schmidt Theorem and its applications to the main eigenvalue problems for the Laplacian.
Gheorghe Moroşanu
semanticscholar +3 more sources
In this chapter we present the main results regarding eigenvalues and eigenvectors of compact and/or symmetric operators. This includes the Hilbert–Schmidt Theorem and its applications to the main eigenvalue problems for the Laplacian.
Gheorghe Moroşanu
semanticscholar +3 more sources
Continuous ZNN Models for Computation of Time-Varying Eigenvalues and Corresponding Eigenvectors
2020 IEEE International Conference on Mechatronics and Automation (ICMA), 2020Computation of eigenvalues as well as corresponding eigenvectors of a time-varying matrix (i.e., with time-dependent elements) is attractive. A continuous Zhang neural network (ZNN) model is developed for computing the eigenvalues and corresponding ...
Min Yang +5 more
semanticscholar +1 more source
International Journal for Numerical Methods in Engineering, 2020
It is well known that the sensitivity analysis of the eigenvectors corresponding to multiple eigenvalues is a difficult problem. The main difficulty is that for given multiple eigenvalues, the eigenvector derivatives can be computed for a specific ...
G. Yoon +3 more
semanticscholar +1 more source
It is well known that the sensitivity analysis of the eigenvectors corresponding to multiple eigenvalues is a difficult problem. The main difficulty is that for given multiple eigenvalues, the eigenvector derivatives can be computed for a specific ...
G. Yoon +3 more
semanticscholar +1 more source
2010
Given a square matrix \( {\rm A} \in \mathbb{C}^{{n \times n}} \), the eigenvalue problem consists in finding a scalar λ (real or complex) and a nonnull vector x such that $${\rm Ax} = \lambda{\rm x}$$ (6.1) Any such λ is called an eigenvalue of A, while x is the associated eigenvector.
Alfio Quarteroni +2 more
openaire +2 more sources
Given a square matrix \( {\rm A} \in \mathbb{C}^{{n \times n}} \), the eigenvalue problem consists in finding a scalar λ (real or complex) and a nonnull vector x such that $${\rm Ax} = \lambda{\rm x}$$ (6.1) Any such λ is called an eigenvalue of A, while x is the associated eigenvector.
Alfio Quarteroni +2 more
openaire +2 more sources