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Geometric fusion via joint delay embeddings

Publication ,  Journal Article
Solomon, E; Bendich, P
Published in: Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020
July 1, 2020

We introduce geometric and topological methods to develop a new framework for fusing multi-sensor time series. This framework consists of two steps: (1) a joint delay embedding, which reconstructs a high-dimensional state space in which our sensors correspond to observation functions, and (2) a simple orthogonalization scheme, which accounts for tangencies between such observation functions, and produces a more diversified geometry on the embedding space. We conclude with some synthetic and real-world experiments demonstrating that our framework outperforms traditional metric fusion methods.

Duke Scholars

Published In

Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020

DOI

Publication Date

July 1, 2020
 

Citation

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Solomon, E., & Bendich, P. (2020). Geometric fusion via joint delay embeddings. Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020. https://doi.org/10.23919/FUSION45008.2020.9190173
Solomon, E., and P. Bendich. “Geometric fusion via joint delay embeddings.” Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020, July 1, 2020. https://doi.org/10.23919/FUSION45008.2020.9190173.
Solomon E, Bendich P. Geometric fusion via joint delay embeddings. Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020. 2020 Jul 1;
Solomon, E., and P. Bendich. “Geometric fusion via joint delay embeddings.” Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020, July 2020. Scopus, doi:10.23919/FUSION45008.2020.9190173.
Solomon E, Bendich P. Geometric fusion via joint delay embeddings. Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020. 2020 Jul 1;

Published In

Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020

DOI

Publication Date

July 1, 2020