Examples of eigenvector

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Ideal pure shear is characterized by a stretching eigenvector parallel to the shear zone boundaries, and a perpendicular shortening eigenvector.
Eigenvector coefficients in factor analysis describe the multidimensional correlated response in these traits to selection for rate of development at different stages of postnatal ontogeny.
At lowest order, the perturbation analysis yields the eigenvalues and eigenvector s for short-wavelength waves, as well as the equations for the background flow.
The left eigenvector s in general have no real physical meaning.
In the following discussion, it is very important to note that the eigenvector y in either the locking or purging need not be accurate.
The solution of the correction equation defines an orthogonal correction for the current eigenvector approximation.
This changes the possible eigenvector sets available to the state vector but in different ways.
The eigenvalues and eigenvector s are those of one dimensional compressible fluid dynamics, namely the forward and backward sound waves and contact discontinuity solutions.
If a unitary action has an eigenvector, then its weakly wandering vectors are clearly not dense.
A sample of 622 daylight spectra was taken, and subjected to an eigenvector analysis.
Instead, we take the (generalized) eigenvector associated with the positive (generalized) eigenvalue that is closest to but distinct from zero.
Accordingly, it implies that the larger the priority eigenvector is, the stronger the correlation between relevant elements can be.
Let us prove that there exists such an eigenvector.
Our previous calculations of steady waves avoided this difficulty by limiting attention to symmetrical solutions, which this eigenvector is obviously not.
Possible field values behind a rarefaction wave are given by the integral curve which follows the eigenvector s of the hyperbolic system.
In practice, we solve a corresponding generalized eigenvector problem using a finite collection of basis functions.
However, in this case it is advantageous to use a left eigenvector to obtain the deflation.
If such a nonnegative matrix has positive maximal eigenvector, it can be reduced to a stochastic matrix by diagonal similarity transformation.
The eigenvector v1 is parallel to the 0 invariant line.

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