Neural-inspired sensors enable sparse, efficient classification of spatiotemporal data [Neuroscience]

Sparse sensor placement is a central challenge in the efficient characterization of complex systems when the cost of acquiring and processing data is high. Leading sparse sensing methods typically exploit either spatial or temporal correlations, but rarely both. This work introduces a sparse sensor optimization that is designed to leverage...

Source: Proceedings of the National Academy of Sciences - October 16, 2018 Category: Science Authors: Thomas L. Mohren, Thomas L. Daniel, Steven L. Brunton, Bingni W. Brunton Tags: Physical Sciences Source Type: research