In physical science, sensor data are collected over time to produce timeseries data. However, depending on the real-world condition and underlying physics of the sensor, data might be noisy. Besides, the limitation of sample-time on sensors may not allow collecting data over all the timepoints, may require some form of interpolation. Interpolation may not be smooth enough, fail to denoise data, and derivative operation on noisy sensor data may be poor that do not reveal any high order dynamics. In this article, we propose to use AutoEncoder to perform interpolation that also denoise data simultaneously. A brief example using a real-world is also provided.
翻译:在物理科学中,传感器数据是随着时间的推移而收集的,以便产生时间序列数据,然而,视传感器真实世界状况和基本物理状况而定,数据可能会很吵。此外,传感器样本时间的限制可能不允许在所有时间点收集数据,可能需要某种形式的内插。内插可能不够顺利,无法提供隐蔽数据,而噪音传感器数据的衍生操作可能较差,无法显示任何高顺序动态。在本篇文章中,我们提议使用AutoEnccoder进行内插,同时进行内插数据。还提供了使用真实世界的简单例子。