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Polygon decomposition is applied in several areas: [1] Pattern recognition techniques extract information from an object in order to describe, identify or classify it. An established strategy for recognising a general polygonal object is to decompose it into simpler components, then identify the components and their interrelationships and use this information to determine the shape of the object.
Manifold decomposition works in two directions: one can start with the smaller pieces and build up a manifold, or start with a large manifold and decompose it. The latter has proven a very useful way to study manifolds: without tools like decomposition, it is sometimes very hard to understand a manifold.
Comment: there are two versions of this decomposition: complex and real. Decomposition (complex version): A = Q S Z ∗ {\displaystyle A=QSZ^{*}} and B = Q T Z ∗ {\displaystyle B=QTZ^{*}} where Q and Z are unitary matrices , the * superscript represents conjugate transpose , and S and T are upper triangular matrices.
Let A be a square n × n matrix with n linearly independent eigenvectors q i (where i = 1, ..., n).Then A can be factored as = where Q is the square n × n matrix whose i th column is the eigenvector q i of A, and Λ is the diagonal matrix whose diagonal elements are the corresponding eigenvalues, Λ ii = λ i.
The restriction in the definition to polynomials of degree greater than one excludes the infinitely many decompositions possible with linear polynomials. Joseph Ritt proved that m = n {\displaystyle m=n} , and the degrees of the components are the same up to linear transformations, but possibly in different order; this is Ritt's polynomial ...
An LU factorization refers to expression of A into product of two factors – a lower triangular matrix L and an upper triangular matrix U: =. Sometimes factorization is impossible without prior reordering of A to prevent division by zero or uncontrolled growth of rounding errors hence alternative expression becomes: P A Q = L U {\displaystyle ...
The Characteristic Set Method is the first factorization-free algorithm, which was proposed for decomposing an algebraic variety into equidimensional components. Moreover, the Author, Wen-Tsun Wu, realized an implementation of this method and reported experimental data in his 1987 pioneer article titled "A zero structure theorem for polynomial equations solving". [1]
A multi-way graph with K perspectives is a collection of K matrices ,..... with dimensions I × J (where I, J are the number of nodes). This collection of matrices is naturally represented as a tensor X of size I × J × K. In order to avoid overloading the term “dimension”, we call an I × J × K tensor a three “mode” tensor, where “modes” are the numbers of indices used to index ...