锥原子稀疏表示

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI:10.1109/icassp49357.2023.10095127

Denis C. Ilie-Ablachim, Andra Baltoiu, Bogdan Dumitrescu

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引用次数: 0

摘要

我们将稀疏表示的概念推广到原子不是向量而是锥的情况，因此是无限集。像往常一样，稀疏表示是线性的，但从每个选定的锥中选择最方便的向量。给出了一种圆锥型的正交匹配寻优算法，并证明了其复杂度仅比正交匹配寻优算法大几倍。新型锥形OMP可用于异常检测;我们将其应用于异常心跳的检测，取得了很好的效果。

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Sparse Representations with Cone Atoms

We extend the notion of sparse representation to the case where the atoms are not vectors, but cones, hence infinite sets. The sparse representation is linear, as usual, but the most convenient vector is chosen from each selected cone. We give a cone version of Orthogonal Matching Pursuit (OMP) and show that its complexity is only a few times larger than that of OMP. The new cone OMP can be used for anomaly detection; we apply it with very good results to the detection of abnormal heartbeats.

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ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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