A New Multivariate Markov Chain Model for Adding a New Categorical Data Sequence

被引：1
|
作者：
Wang, Chao [1 ]
Huang, Ting-Zhu [1 ]
Ching, Wai-Ki [2 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Sichuan, Peoples R China
[2] Univ Hong Kong, Dept Math, Adv Modeling & Appl Comp Lab, Hong Kong, Hong Kong, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2014年 / 2014卷
关键词：
D O I：
10.1155/2014/502808
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
We propose a new multivariate Markov chain model for adding a new categorical data sequence. The number of the parameters in the new multivariate Markov chain model is only partial derivative(3s) less than partial derivative((s + 1)(2)) the number of the parameters in the former multivariate Markov chain model. Numerical experiments demonstrate the benefits of the new multivariate Markov chain model on saving computational resources.
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页数：8
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