反馈延迟手动追踪的负群延迟模型
A negative group delay model for feedback-delayed manual tracking
AI总结：
本研究提出反馈延迟手动追踪表现受负群延迟物理约束限制，用含单个自由参数的延迟诱导负群延迟线性系统建模，解释了实验关键观测结果并给出可验证的定量预测。
摘要：
我们提出，反馈延迟下的手动追踪表现受负群延迟物理学基本约束的限制。为验证这一假设，我们将一项实验的结果（受试者在实验中表现出反应性和预测性两种动力学特征）用具有延迟诱导负群延迟的线性系统建模。尽管这是可设想的最简单的实时预测器之一，该模型仍能解释实验观测的关键组成部分。最值得注意的是，它解释了预测时间随反馈延迟线性增长，直至追踪表现恶化的某一临界点的观测结果；也解释了随着反馈延迟增加，行为从反应性向预测性转变的现象。该模型仅包含一个自由参数——反馈增益，已通过与反应性情形下的一组实验观测对比确定。我们的模型给出了可在后续实验中验证的定量预测。
英文摘要：
We propose that feedback-delayed manual tracking performance is limited by fundamental constraints imposed by the physics of negative group delay. To test this hypothesis, the results of an experiment in which subjects demonstrate both reactive and predictive dynamics are modeled by a linear system with delay-induced negative group delay. Although one of the simplest real-time predictors conceivable, this model explains key components of experimental observations. Most notably, it explains the observation that prediction time linearly increases with feedback delay, up to a certain point when tracking performance deteriorates. It also explains the transition from reactive to predictive behavior with increasing feedback delay. The model contains only one free parameter, the feedback gain, which has been fixed by comparison with one set of experimental observations for the reactive case. Our model provides quantitative predictions that can be tested in further experiments.
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