Search Results for author:
Found 2 papers, 1 papers with code
Applicability and interpretation of the deterministic weighted cepstral distance
In this way, we provide a purely data-driven way to assess different underlying dynamics of input/output signal pairs, without the need for any system identification step.
A time series distance measure for efficient clustering of input output signals by their underlying dynamics
The first class of methods employs a distance measure on time series (e. g. Euclidean, Dynamic Time Warping) and a clustering technique (e. g. k-means, k-medoids, hierarchical clustering) to find natural groups in the dataset.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
