论文标题
公理A吸引子的统计推断
Statistical inference for Axiom A attractors
论文作者
论文摘要
从气候系统到互联网对社会的影响，混乱系统似乎在我们的未来中起着重要作用。在这里，描述了一类混沌系统的统计学习方法以及基本理论，该理论不仅可以用于预测这些系统的短时间，而且还可以用作对其动力学的统计推断的基础。该方法应用于3种不同系统的预测。统计推断方面可以应用于探索和增强此类系统的计算机模型，从而为更好的预测和更精确的推断提供反馈。
From the climate system to the effect of the internet on society, chaotic systems appear to have a significant role in our future. Here a method of statistical learning for a class of chaotic systems is described along with underlying theory that can be used not only for predicting those systems a short time ahead, but also as a basis for statistical inference about their dynamics. The method is applied to prediction of 3 different systems. The statistical inference aspect can be applied to explore and enhance computer models of such systems which in turn can provide feedback for even better prediction and more precise inference.
