Search results
Results from the WOW.Com Content Network
In mathematics, the Kronecker product, sometimes denoted by ⊗, is an operation on two matrices of arbitrary size resulting in a block matrix.It is a specialization of the tensor product (which is denoted by the same symbol) from vectors to matrices and gives the matrix of the tensor product linear map with respect to a standard choice of basis.
The Kronecker sum is different from the direct sum, but is also denoted by ⊕. It is defined using the Kronecker product ⊗ and normal matrix addition. If A is n -by- n , B is m -by- m and I k {\displaystyle \mathbf {I} _{k}} denotes the k -by- k identity matrix then the Kronecker sum is defined by:
Based on this, eigenvalues and eigenvectors of the Kronecker sum can also be explicitly calculated. The eigenvalues and eigenvectors of the standard central difference approximation of the second derivative on an interval for traditional combinations of boundary conditions at the interval end points are well known .
The map , representing scalar multiplication as a sum of outer products. The generalized Kronecker delta or multi-index Kronecker delta of order 2 p {\displaystyle 2p} is a type ( p , p ) {\displaystyle (p,p)} tensor that is completely antisymmetric in its p {\displaystyle p} upper indices, and also in its p {\displaystyle p} lower indices.
The outer product and Kronecker product are closely related; in fact the same symbol is commonly used to denote both operations. ... Then can be expressed as a sum of ...
The motivation for the use of the Kronecker sum in this definition comes from the case in which and come from representations and of a Lie group. In that case, a simple computation shows that the Lie algebra representation associated to Π 1 ⊗ Π 2 {\displaystyle \Pi _{1}\otimes \Pi _{2}} is given by the preceding formula.
The discrete Laplacian is defined as the sum of the second derivatives and calculated as sum of differences over the nearest neighbours of the central pixel. Since derivative filters are often sensitive to noise in an image, the Laplace operator is often preceded by a smoothing filter (such as a Gaussian filter) in order to remove the noise ...
These formulas are used to derive the expressions for eigenfunctions of Laplacian in case of separation of variables, as well as to find eigenvalues and eigenvectors of multidimensional discrete Laplacian on a regular grid, which is presented as a Kronecker sum of discrete Laplacians in one-dimension.