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Signal Processing on Cell Complexes

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arxiv 2110.05614 v2 pith:T5BG45NE submitted 2021-10-11 cs.LG cs.SIeess.SPmath.ATmath.GT

classification cs.LGcs.SIeess.SPmath.ATmath.GT
keywords complexescellprocessingsignalsbeendomainsfilteringgraphs
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The processing of signals supported on non-Euclidean domains has attracted large interest recently. Thus far, such non-Euclidean domains have been abstracted primarily as graphs with signals supported on the nodes, though the processing of signals on more general structures such as simplicial complexes has also been considered. In this paper, we give an introduction to signal processing on (abstract) regular cell complexes, which provide a unifying framework encompassing graphs, simplicial complexes, cubical complexes and various meshes as special cases. We discuss how appropriate Hodge Laplacians for these cell complexes can be derived. These Hodge Laplacians enable the construction of convolutional filters, which can be employed in linear filtering and non-linear filtering via neural networks defined on cell complexes.

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Cited by 1 Pith paper

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  1. Topological Neural Networks over the Air

    cs.IT 2025-02 conditional novelty 4.0 of 10

    AirTNN treats wireless channel fading and noise as part of the topological convolutional filter, improving robustness over graph-based and communication-agnostic baselines in synthetic source localization.

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