Abstract
Uniform embedding techniques have limitations for the reconstruction of the phase space of nonlinear time series whose dynamics is not completely known, so new embedding techniques have been developed based on non-uniform methodologies. This work compares the reconstruction quality supported by the Uzal cost function, of three electrocardiography databases. For the uniform reconstruction, Average Mutual Information was implemented to find the time delay (\(\tau \)) and False Nearest Neighbor and Average False Neighbor were tested to find the attractor dimension (m). For the non-uniform reconstruction, the algorithm of Hankel Singular Value Decomposition was implemented. The results showed that the non-uniform embedding, based on Hankel Singular Value Decomposition, provides a better quality in the reconstruction of the phase space.
This work is presented in partial fulfillment of the requirements for the “Call for the strengthening of vocations and training in ST&I for economic reactivation in the framework of the 2020 post-pandemic” No. 891 of MinCiencias- Colombia.
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Restrepo-Uribe, J.P., Orrego-Metaute, D.A., Delgado-Trejos, E., Cuesta-Frau, D. (2022). Uniform and Non-uniform Embedding Quality Using Electrocardiographic Signals. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications. IWINAC 2022. Lecture Notes in Computer Science, vol 13258. Springer, Cham. https://doi.org/10.1007/978-3-031-06242-1_60
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