2019
Time Signal Classification Using Random Convolutional Features
ICASSP 2019accepted
In this paper we present a transformation to convert time signals into a randomized low-dimensional vectors such that the inner product between these new features provides information about the similarity of the signals. We show that the described inner product approximates a cross-correlation based…