|
A factor graph is a bipartite graph representing the factorization of a function. In probability theory and its applications, factor graphs are used to represent factorization of a probability distribution function, enabling efficient computations, such as the computation of marginal distributions through the sum-product algorithm. One of the important success stories of factor graphs and the sum-product algorithm is the decoding of capacity-approaching error-correcting codes, such as LDPC and turbo codes. Factor graphs generalize constraint graphs. A factor whose value is either 0 or 1 is called a constraint. A constraint graph is a factor graph where all factors are constraints. The max-product algorithm for factor graphs can be viewed as a generalization of the arc-consistency algorithm for constraint processing. ==Definition== A factor graph is a bipartite graph representing the factorization of a function. Given a factorization of a function , : where , the corresponding factor graph consists of variable vertices , factor vertices , and edges . The edges depend on the factorization as follows: there is an undirected edge between factor vertex and variable vertex iff . The function is tacitly assumed to be real-valued: . Factor graphs can be combined with message passing algorithms to efficiently compute certain characteristics of the function , such as the marginal distributions. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「factor graph」の詳細全文を読む スポンサード リンク
|