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The Laplace expansion is computationally inefficient for high-dimension matrices, with a time complexity in big O notation of O(n!). Alternatively, using a decomposition into triangular matrices as in the LU decomposition can yield determinants with a time complexity of O(n 3). [2] The following Python code implements the Laplace expansion:
The cofactors feature prominently in Laplace's formula for the expansion of determinants, which is a method of computing larger determinants in terms of smaller ones. Given an n × n matrix A = ( a ij ) , the determinant of A , denoted det( A ) , can be written as the sum of the cofactors of any row or column of the matrix multiplied by the ...
Boole's expansion theorem, often referred to as the Shannon expansion or decomposition, is the identity: = + ′ ′, where is any Boolean function, is a variable, ′ is the complement of , and and ′ are with the argument set equal to and to respectively.
The basic idea from which the data structure was created is the Shannon expansion. A switching function is split into two sub-functions (cofactors) by assigning one variable (cf. if-then-else normal form). If such a sub-function is considered as a sub-tree, it can be represented by a binary decision tree.
Cofactor expansion. Add languages. Add links. Article; Talk; ... Download QR code; Print/export Download as PDF; Printable version; In other projects
In linear algebra, the adjugate or classical adjoint of a square matrix A, adj(A), is the transpose of its cofactor matrix. [1] [2] It is occasionally known as adjunct matrix, [3] [4] or "adjoint", [5] though that normally refers to a different concept, the adjoint operator which for a matrix is the conjugate transpose.
In Boolean logic, a Reed–Muller expansion (or Davio expansion) is a decomposition of a Boolean function. For a Boolean function f ( x 1 , … , x n ) : B n → B {\displaystyle f(x_{1},\ldots ,x_{n}):\mathbb {B} ^{n}\to \mathbb {B} } we call
(Laplace expansion provides a formula for computing the , but their expression is not important here.) If the function D j {\displaystyle D_{j}} is applied to any other column k of A , then the result is the determinant of the matrix obtained from A by replacing column j by a copy of column k , so the resulting determinant is 0 (the case of two ...