Examples of 'laplacian' in a sentence
Meaning of "laplacian"
laplacian (noun) - In the context of mathematics or physics, the term Laplacian often refers to a differential operator
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- Of, or relating to Laplace.
- The Laplace operator.
- Alternative letter-case form of Laplacian
How to use "laplacian" in a sentence
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laplacian
Regularized trace of the inverse of the dirichlet laplacian.
Laplacian stack of the lion.
The divergence of the gradient is called the LaPlacian.
Laplacian of Gaussian is often impractical because it is inefficient.
The variable coefficients can be viewed as a generalization of the laplacian operator.
The Laplacian is given above in terms of spherical polar coordinates.
It needs special consideration because it involves the laplacian differential operator.
The Laplacian matrix can be used to find many useful properties of a graph.
The nonlinearities are supposed to interact only with k eigenvalues of the free laplacian.
Fundamental solution for the Laplacian in n dimension.
A charge shift bond is expected to have a positive or small Laplacian.
Chaos theory eliminates the Laplacian illusion of deterministic predictability.
You will learn exciting terms like maximum likelihood estimator and laplacian estimator.
We consider a Laplacian on a directed weighted graph with non symmetric edge weights.
I really want you to remember Laplacian smoothing.
See also
The determination of a Laplacian operator can be realized in an electronic manner with simple means.
This defines quantum resonances for this Laplacian.
Its use to represent the Laplacian should not be confused with this use.
One example of such distribution being the Laplacian distribution.
The perceived deficiencies of the Laplacian model stimulated scientists to find a replacement for it.
Select here the sharpen deviation value of the Laplacian.
The traces of powers of a Laplacian can be used to define the Selberg zeta function.
These frequencies are the eigenvalues of the Laplacian in the space.
Other detectors uses a Laplacian estimator which is the determinant of the Hessian matrix.
This scale correspond to a maximum over scale of a Laplacian operator.
The remaining Laplacian images are processed in this manner until the original image is reconstructed.
A combination of gradient and divergence produces the Laplacian of a scalar function.
So let us not assume we have Laplacian smoothing and instead use the maximum likelihood estimator.
And the probability density of the source is assumed to follow a Laplacian distribution.
The same approach implies that the Laplacian of the gravitational potential is the mass distribution.
It is used together with the adjacency matrix to construct the Laplacian matrix of a graph.
The vector Laplacian is similar to the scalar Laplacian.
The exact definition of the algebraic connectivity depends on the type of Laplacian used.
Thrun So in Laplacian smoothing we look at the relative counts.
It approximates the sparsest cut of a graph through the second eigenvalue of its Laplacian.
This concept has long been utilized for the Laplacian in two and three dimensions.
This is revealed by topological analysis of the electron density distribution and its associated Laplacian.
This thesis concerns the solution of finite element discretised Laplacian eigenvalue problems of coupled systems.
This thesis deals also with questions of specral theory of finite triangulations on our Laplacian.
The Laplacian alone will not do.
This quantization technique is applied mainly in respect of data with a Laplacian distribution characteristic.
The Laplacian in differential geometry.
Another part of this thesis consist to study the spectral properties of the Laplacian operator.
And the Laplacian is given by.
In one version the statistical model assumes the MDCT lines are independent and Laplacian distributed.
Scores are refined using a ratio of Laplacian of Gaussian convolution responses.
The several captured images can represent a Gaussian pyramid or a Laplacian pyramid.
P is the Laplacian operator.
One can also obtain the Laplacian.
Clumped objects were identified using Laplacian of Gaussian modeling and separated by shape.
