对于离散时间切换的基因调节网络的状态边界,具有时间延迟和外源干扰
Jiayuan Yan1, Bin Hu2, Zhi-Hong Guan3
1School of Artificial Intelligence, Henan University, Zhengzhou, 450046, China.
概括
这项研究估计了离散时间切换的基因调节网络的状态边界,具有时间延迟和干扰. 平均停留时间方法确保了对多类型的指数趋同,与传统方法相比简化了分析.
科学领域:
- 系统生物学 系统生物学
- 控制理论 控制理论
- 计算神经科学是一种神经科学.
背景情况:
- 遗传调节网络 (GRNs) 对于细胞功能至关重要.
- 用离散时间切换动态 (DSGRNs) 建模GRNs,由于时间延迟和外部干扰,这会带来挑战.
- 准确的状态界限对于分析这些复杂的生物系统的稳定性和行为至关重要.
研究的目的:
- 开发一种可靠的方法,用于DSGRNs中的状态边界估计.
- 解决时间延迟和局限外源干扰的系统.
- 为稳定性分析提供简化标准,特别是在零干扰或初始条件等特殊情况下.
主要方法:
- 引入特定的系统参数假设来制定边界多型.
- 应用平均停留时间 (ADT) 方法与数学诱导相结合,用于收分析.
- 利用Metzler和非负矩阵的杆性质来导出简要的状态界限标准.
主要成果:
- 证明了DSGRN解决方案的指数趋同到一个定义的多型.
- 在没有干扰的情况下,为全球指数稳定性建立了足够的条件.
- 引入了一个多类型,以限制零初始条件的系统轨迹,从而产生了简化的标准.
结论:
- 提出的基于ADT的方法有效地限制了一般化DSGRNs中的状态,克服了现有方法的局限性.
- 这项研究为稳定性分析提供了一个比Lyapunov函数式方法更易于计算的替代方案.
- 理论发现通过数值模拟得到验证,证实了开发的状态限制技术的有效性.
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