Examples of 'eigenvalue' in a sentence
Meaning of "eigenvalue"
eigenvalue (noun) - In mathematics, specifically linear algebra, an eigenvalue represents a scalar that is associated with a non-zero vector in the context of a linear transformation
Show more definitions
- A scalar, λ, such that there exists a non-zero vector x (a corresponding eigenvector) for which the image of x under a given linear operator A is equal to the image of x under multiplication by λ; i.e. Ax=λx.
How to use "eigenvalue" in a sentence
Basic
Advanced
eigenvalue
It can be understood as the eigenvalue of a charge operator.
The eigenvalue concept is not restricted to energy.
A natural way to do this is by eigenvalue analysis of a matrix.
Each component will yield a corresponding eigenvalue.
These eigenvalue algorithms may also find eigenvectors.
The resulting equation is known as eigenvalue equation.
The rightmost eigenvalue is the most unstable one.
Solution of linear systems and eigenvalue problems.
Lambda indicates an eigenvalue in the mathematics of linear algebra.
Numerical methods of solving eigenvalue problems.
The eigenvalue condition is not sufficient for solvability.
Lambda is truly an eigenvalue of our matrix.
The eigenvalue decomposition is cached internally.
Numerical modelling results in eigenvalue problems of large sizes.
And they are the eigenvectors that correspond to eigenvalue.
See also
Its eigenvalue will be the constant degree of the graph.
The vector converges to an eigenvector of the largest eigenvalue.
With the energy eigenvalue and.
The last eigenvalue depends on the studied degree of freedom.
The value λ is the corresponding eigenvalue.
Corresponding to each eigenvalue there are a finite number of degenerate states.
And the lambda is called an eigenvalue.
This follows by considering the eigenvalue decompositions of both matrices.
Notice that the vector x is an eigenvector to the corresponding eigenvalue λ.
Observations on eigenvalue buckling analysis within a finite element context.
Has at least one complex eigenvalue.
The eigenvalue is off.
Solution of coupled acoustic eigenvalue problems.
The eigenvalue of the operator is the position vector of the particle.
These equations are a generalized eigenvalue problem.
The eigenvalue algorithm can then be applied to the restricted matrix.
That a matrix satisfies its own eigenvalue equation.
The dominant eigenvalue can be easily estimated for any matrix.
The position of the minimization is the lowest reliable eigenvalue.
Moser iteration and a nonlinear eigenvalue problem on metric spaces.
Eigenvalue problems for ODEs are similarly converted to matrix eigenvalue problems.
The associated eigenvalue problem is.
For each eigenvalue there are one or more corresponding eigenvectors eigenstates.
Considering the eigenvalue problem.
This will quickly converge to the eigenvector of the closest eigenvalue to μ.
We consider the eigenvalue problem.
In other words there is precisely one block per distinct eigenvalue.
Which is a standard eigenvalue problem.
Ap being the eigenvalue of rank p of the matrix generated in the first phase.
That really is called an eigenvalue.
The method proceeds by the eigenvalue decomposition of the kernel matrix.
Not to be confused with eigenvalue.
The corresponding eigenvalue gives the number of particles in the state.
Derivative of a generalized eigenvalue problem.
Matrix eigenvalue problem.
