多慢才算慢？SFA检测比驱动力慢的信号
How slow is slow? SFA detects signals that are slower than the driving force
摘要：
慢特征分析（SFA）是一种从快速变化的非平稳时间序列中提取慢变化驱动力的方法。我们在这里表明，它是可能的SFA检测到一个组件，甚至比驱动力本身（例如调制正弦波的包络）慢。它示出，它取决于像嵌入维数，时间序列的可预测性，或基础频率的情况下，无论是驱动力本身或较慢的子分量被检测到。我们观察到从一个政权到其他的相变，这是这项工作的目的，量化的各种参数对这种相变的影响。我们的结论是，什么是感知为慢的SFA变化，或多或少快速切换从一个政权到另一个发生，也许表现出一些相似的人类感知。
英文摘要：
Slow feature analysis (SFA) is a method for extracting slowly varying driving forces from quickly varying nonstationary time series. We show here that it is possible for SFA to detect a component which is even slower than the driving force itself (e.g. the envelope of a modulated sine wave). It is shown that it depends on circumstances like the embedding dimension, the time series predictability, or the base frequency, whether the driving force itself or a slower subcomponent is detected. We observe a phase transition from one regime to the other and it is the purpose of this work to quantify the influence of various parameters on this phase transition. We conclude that what is percieved as slow by SFA varies and that a more or less fast switching from one regime to the other occurs, perhaps showing some similarity to human perception.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
