动态独立:在复杂的动态系统中发现新出现的宏观过程
1Sussex Centre for Consciousness Science, Department of Informatics, University of Sussex, Falmer, Brighton BN1 9QJ, United Kingdom.
Physical review. E
|August 16, 2023
概括
我们引入了一种新的方法来识别复杂系统中的新兴现象. 这种方法量化了动态独立性,以发现具有不同行为的宏观变量,有助于理解多尺度系统.
科学领域:
- 复杂系统科学 复杂系统科学
- 动态系统理论 动态系统理论
- 信息理论 信息理论
背景情况:
- 宏观现象往往源于复杂的多变量微观动态.
- 了解出现需要区分宏观行为与潜在的微观过程.
研究的目的:
- 引入基于动态独立的新兴的定量框架.
- 开发用于发现复杂系统中出现的宏观变量的方法.
- 为了能够创建多尺度的浮现肖像.
主要方法:
- 通过宏观变量的动态独立来定义出现.
- 使用香农基于信息的衡量器来测量动态依赖.
- 为线性系统 (时间和频率领域) 开发显式计算.
- 概述神经生理学时间序列数据的应用.
主要成果:
- 动态依赖的量化提供了一种衡量出现的方法.
- 该框架有助于以数据驱动的方式发现新出现的现象.
- 线性系统分析允许明确计算动态依赖.
- 对于复杂的系统,包括神经系统,可以推断出出现肖像.
结论:
- 动态独立提供了一个严格的定义的出现.
- 提出的方法可以识别和描述新出现的行为.
- 这项工作为分析不同系统的跨时空尺度的出现提供了一条途径.
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