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Directional Statistics in Signal Processing: A Geometry Driven Overview of Models, Learning, and Applications

arXiv:2611.04595v1 Announce Type: cross Abstract: Many signal-processing objects are defined by periodicity, normalization, sign or global-phase ambiguity, basis invariance, or positive-semidefinite constraints and therefore cannot be modeled faithfully in ordinary Euclidean space. This paper devel…

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  1. 2026-11-04 05:00 · arXiv stat.ML
    Directional Statistics in Signal Processing: A Geometry Driven Overview of Models, Learning, and Applications

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