Results 271 to 280 of about 177,680 (311)
Rapid eigenpatch utility classifier for image denoising. [PDF]
Sci RepMitchell MAJ, Sanvito S, Jones L.
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Intermediate scattering function of colloids in a periodic laser field.
Soft MatterRusch R +4 more
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Input-driven circuit reconfiguration in critical recurrent neural networks. [PDF]
Proc Natl Acad Sci U S AMagnasco MO.
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Eigenvalues and eigenvectors [PDF]
, 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 +3 more
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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.
James R. Kirkwood, Bessie H. Kirkwood
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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.
James R. Kirkwood, Bessie H. Kirkwood
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1986
Recall that an n × n matrix B is similar to an n × n matrix A if there is an invertible n × n matrix P such that B = P −1 AP. Our objective now is to determine under what conditions an n × n matrix is similar to a diagonal matrix. In so doing we shall draw together all of the notions that have been previously developed.
T. S. Blyth, Edmund F. Robertson
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Recall that an n × n matrix B is similar to an n × n matrix A if there is an invertible n × n matrix P such that B = P −1 AP. Our objective now is to determine under what conditions an n × n matrix is similar to a diagonal matrix. In so doing we shall draw together all of the notions that have been previously developed.
T. S. Blyth, Edmund F. Robertson
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Eigenvectors and Eigenvalues [PDF]
, 1986 This chapter gives the basic elementary properties of eigenvectors and eigenvalues. We get an application of determinants in computing the characteristic polynomial. In §3, we also get an elegant mixture of calculus and linear algebra by relating eigenvectors with the problem of finding the maximum and minimum of a quadratic function on the sphere ...
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1987
In this chapter we describe numerical techniques for the calculation of a scalar λ and non-zero vector x in the equation $$ Ax = \lambda x $$ (4.1) where A is a given n × n matrix. The quantities λ and x are usually referred to as an eigenvalue and an eigenvector of A.
Colin Judd, Ian Jacques
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In this chapter we describe numerical techniques for the calculation of a scalar λ and non-zero vector x in the equation $$ Ax = \lambda x $$ (4.1) where A is a given n × n matrix. The quantities λ and x are usually referred to as an eigenvalue and an eigenvector of A.
Colin Judd, Ian Jacques
openaire +2 more sources