arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2304.04414math.PRmath.CA
收藏

马尔可夫链与多重正交性

Markov Chains and Multiple Orthogonality

Amílcar Branquinho, Juan E. F. Díaz, Ana Foulquié-Moren, Manuel Mañas

AI总结:

本文综述马尔可夫链与多重正交性理论的联系,提出从Jacobi--Piñeiro等族生成随机四对角Hessenberg矩阵的步骤,并证明正四对角非负有界Hessenberg矩阵可构造两个互为极限转置的随机矩阵。

摘要:

本文综述了马尔可夫链与多重正交性理论的联系。我们主要集中于给出一种生成随机四对角Hessenberg矩阵的步骤,这些矩阵源自特定的多重正交族,如Jacobi--Piñeiro和超几何Lima--Loureiro族。我们证明,对于一个正的四对角非负有界Hessenberg矩阵,可以构造两个随机四对角矩阵。受Poincaré定理启发,这两个随机三对角非负Hessenberg矩阵被证明互为极限转置。

英文摘要:

In this work we survey on connections of Markov chains and the theory of multiple orthogonality. Here we mainly concentrate on give a procedure to generate stochastic tetra diagonal Hessenberg matrices, coming from some specific families of multiple orthogonal, such as the ones of Jacobi--Piñeiro and Hypergeometric Lima--Loureiro. We show that associated with a positive tetra diagonal nonnegative bounded Hessenberg matrix we can construct two stochastic tetra diagonal ones. These two stochastic tridiagonal nonnegative Hessenberg matrices are shown to be, enlightened by the Poincaré theorem, limit transpose of each other.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑