Examples of using Eigenvalue in English and their translations into Greek
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This is a contradiction, andso A has an eigenvalue.
The Sturm-Liouville eigenvalue problem involves a general quadratic form.
Leads to a so-called quadratic eigenvalue problem.
Every eigenvalue of a Unitary matrix has absolute value| λ|= 1.
Leads to what is called a so-called quadratic eigenvalue problem.
An eigenvalue λ of a matrix M is characterized by the algebraic relation Mu= λu.
If A{\displaystyle A} is unitary, every eigenvalue has absolute value| λ i|.
Eigenvalue problems occur naturally in the vibration analysis of mechanical structures with many degreesoffreedom.
For example, once it is known that 6 is an eigenvalue of the matrix.
Which is precisely an eigenvalue equation for f(x){\displaystyle f(x)}, hence the name eigenmode.
They are determined by the unitary maps between the eigenvalue spaces.
We know that a field element is an eigenvalue of if and only if is a root of the characteristic polynomial.
If one wantsto underline this aspect, one speaks of nonlinear eigenvalue problems.
Eigenvalue problems occur naturally in the vibration analysis of mechanical structures with many degrees of freedom.
Several important problems can be phrased in terms of eigenvalue decompositions or singular value decompositions.
J(J+ 1) the eigenvalue for eigenstate J2 for the stationary states within the incomplete atoms shells(electrons unpaired).
The concept behind link analysis is basic,you can represent a chart in a Matrix kind making it a eigenvalue issue.
(Here it is understood that an eigenvalue with algebraic multiplicity μ occurs μ times in this list.).
The blue arrow is an eigenvector of this shear mapping because it doesn't change direction, andsince its length is unchanged, its eigenvalue is 1.
For such cases, for an eigenvalue λ with multiplicity m, the first m- 1 derivative of p(x) vanishes at the eigenvalues. .
Here exp(A) denotes the matrix exponential of A, because every eigenvalue λ of A corresponds to the eigenvalue exp(λ) of exp(A).
Otherwise, by the claim applied to Tn, there is a norm one eigenvector enof T in Hn, with corresponding non-zero eigenvalue λn=± m(Tn).
If n is odd,there is at least one real eigenvalue, +1 or- 1; for a 3× 3 rotation, the eigenvector associated with +1 is the rotation axis.
They are used to define the characteristic polynomial of a matrix that is an essential tool in eigenvalue problems in linear algebra.
Hyperbolic: there is only one negative eigenvalue and all the rest are positive, or there is only one positive eigenvalue and all the rest are negative.
To establish that every complex polynomial of degree n> 0 has a zero, it suffices to show that every complex square matrix of size n>0 has a(complex) eigenvalue.
In the meantime,Liouville studied eigenvalue problems similar to those of Sturm; the discipline that grew out of their work is now called Sturm- Liouville theory.
Moreover, the eigenvectors are not unique because any linear combination of eigenvectors for the same eigenvalue is also an eigenvector for that eigenvalue.
This is the eigenvalue under reflection, and is positive(i.e. +1) for states which came from even l and negative(i.e. -1) for states which came from odd l.
Therefore, any real matrix with odd order has at least one real eigenvalue, whereas a real matrix with even order may not have any real eigenvalues. .
