Search results
Results from the WOW.Com Content Network
Decomposition method is a generic term for solutions of various problems and design of algorithms in which the basic idea is to decompose the problem into subproblems. The term may specifically refer to: Decomposition method (constraint satisfaction) in constraint satisfaction
Decomposition: This is a version of Schur decomposition where and only contain real numbers. One can always write A = V S V T {\displaystyle A=VSV^{\mathsf {T}}} where V is a real orthogonal matrix , V T {\displaystyle V^{\mathsf {T}}} is the transpose of V , and S is a block upper triangular matrix called the real Schur form .
According to Booch, algorithmic decomposition is a necessary part of object-oriented analysis and design, but object-oriented systems start with and emphasize decomposition into objects. [ 2 ] More generally, functional decomposition in computer science is a technique for mastering the complexity of the function of a model.
In mathematics, a polynomial decomposition expresses a polynomial f as the functional composition of polynomials g and h, where g and h have degree greater than 1; it is an algebraic functional decomposition. Algorithms are known for decomposing univariate polynomials in polynomial time.
In algebra, the partial fraction decomposition or partial fraction expansion of a rational fraction (that is, a fraction such that the numerator and the denominator are both polynomials) is an operation that consists of expressing the fraction as a sum of a polynomial (possibly zero) and one or several fractions with a simpler denominator.
Permutation decomposition, decomposition of a permutation into disjoint cycles; Primary decomposition, decomposition of ideals into primary ideals; Vector decomposition, decomposition of vectors into components or coordinates of basis vectors; Wavelet decomposition, re-expressing a given function as the sum of a series of wavelet functions
Benders decomposition (or Benders' decomposition) is a technique in mathematical programming that allows the solution of very large linear programming problems that have a special block structure. This block structure often occurs in applications such as stochastic programming as the uncertainty is usually represented with scenarios.
The decomposition depicted in the figure below is this special decomposition for the given graph. A graph, its quotient where "bags" of vertices of the graph correspond to the children of the root of the modular decomposition tree, and its full modular decomposition tree: series nodes are labeled "s", parallel nodes "//" and prime nodes "p".