通过潜在的随机动态系统的早期预警指标.
Lingyu Feng1,2,3, Ting Gao1,2,3, Wang Xiao1,2,3
1School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan 430074, China.
Chaos (Woodbury, N.Y.)
|March 5, 2024
概括
这项研究引入了一种新方法,用于检测复杂系统突然变化的早期预警信号. 该方法成功地确定了脑电图数据中的临界点,有助于早期发现疾病.
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
- 生物医学数据分析
背景情况:
- 复杂系统中的突然动态转换在诸如脑部疾病和自然灾害等领域构成风险.
- 早期发现这些转变对于及时干预和缓解至关重要.
- 现有的方法经常与高维或潜伏动态作斗争.
研究的目的:
- 开发一种新的框架,用于检测突发动态转变的早期预警指标.
- 从高维数据中捕捉低维多元中的潜在进化动态.
- 为了导出和验证状态转换的有效警告信号.
主要方法:
- 开发了一种定向的异构扩散地图,以揭示潜在的动态.
- 导出了三个警告信号:Onsager-Machlup,样本和过渡概率指标.
- 将框架应用于真实的脑电图 (EEG) 数据进行验证.
主要成果:
- 拟议的框架成功地确定了EEG数据状态转换期间的临界点.
- 衍生出来的早期预警指标证明了检测关键过渡点的能力.
- 该方法有效地将潜伏动态与现实世界时间序列数据联系起来.
结论:
- 新的框架为突然的动态转变提供了有效的早期预警指标.
- 这种方法显示了复杂的高维时间序列的自动标记的潜力.
- 这些发现对预测各种复杂系统 (包括神经系统疾病) 中的关键事件有意义.
相关概念视频
Linear time-invariant Systems
258
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
258
Second Order systems II
109
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
109
Stability
125
The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
125
Linear Approximation in Time Domain
81
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
81
First Order Systems
90
First-order systems, such as RC circuits, are foundational in understanding dynamic systems due to their straightforward input-output relationship. Analyzing their responses to different input functions under zero initial conditions reveals significant insights into system behavior.
When a first-order system is subjected to a unit-step input, its response is characterized by its transfer function. By applying the Laplace transform of the unit-step input to the transfer function, expanding the...
When a first-order system is subjected to a unit-step input, its response is characterized by its transfer function. By applying the Laplace transform of the unit-step input to the transfer function, expanding the...
90
Classification of Systems-I
186
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
186


