论文标题
数据驱动的分布式缓解策略和突变流行过程的分析
Data-Driven Distributed Mitigation Strategies and Analysis of Mutating Epidemic Processes
论文作者
论文摘要
在本文中，我们研究了一个离散的SIS（易感感染感染）模型，其中感染和康复参数以及基础网络可能会随着时间而变化。我们为模型提供了明确定义并研究其稳定性的条件。对于具有对称图的均质感染率的系统，我们为健康状态的全球指数稳定性（GES）提供了足够的条件，即消除病毒的地方。对于具有异质性病毒的系统分布在有向图上的系统，只要变异不太快，就可以建立足够的健康状态状态条件。
In this paper we study a discrete-time SIS (susceptible-infected-susceptible) model, where the infection and healing parameters and the underlying network may change over time. We provide conditions for the model to be well-defined and study its stability. For systems with homogeneous infection rates over symmetric graphs,we provide a sufficient condition for global exponential stability (GES) of the healthy state, that is, where the virus is eradicated. For systems with heterogeneous virus spread over directed graphs, provided that the variation is not too fast, a sufficient condition for GES of the healthy state is established.
