Extensive investigations and interdisciplinary design considerations, including a DNNbased autoencoder structure, learning framework, and implementation of a low-complexity digital circuit for ...

Slow feature analysis aims to linearly transform measured data into uncorrelated signals that vary from slow to fast. While earlier extensions successfully extracted slow features from nonlinear ...