Modeling Markov sources and hidden Markov models by P systems

被引：2
|
作者：
Sempere, Jose M. [1 ]
机构：
[1] Univ Politecn Valencia, Valencian Res Inst Artificial Intelligence VRAIN, Valencia, Spain
来源：
JOURNAL OF MEMBRANE COMPUTING | 2023年 / 5卷 / 03期
关键词：
Transition P systems; Evolution and target rules; Stochastic rules; Markov sources; Hidden Markov models;
D O I：
10.1007/s41965-023-00129-6
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this work, we provide several algorithms to obtain stochastic transition P systems from Markov sources and Hidden Markov Models. In both cases, stochastic P systems are obtained that use probabilistic evolution, send-in and send-out rules. The use of objects and the structure of membranes correspond to the states of the Markov sources and the Hidden Markov Models. This proposal is especially useful to use P systems to model complex systems with a stochastic behavior.
引用
收藏
页码：161 / 169
页数：9
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