自相关时间序列的凸聚类

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2022-05-23 DOI:10.1109/icassp43922.2022.9747143

Max Revay, V. Solo

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引用次数: 0

摘要

虽然聚类通常是一个研究较多的领域，但自相关时间序列(CATS)的聚类却很少受到关注。在这里，我们开发了一种适合于自相关时间序列的凸聚类算法，并将其与最先进的方法进行了比较。我们发现该算法能够更准确地识别出真实的聚类。

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Convex Clustering for Autocorrelated Time Series

While clustering in general is a heavily worked area, clustering of auto-correlated time series (CATS) has received relatively little attention. Here, we develop a convex clustering algorithm suited to auto-correlated time series and compare it with a state of the art method. We find the proposed algorithm is able to more accurately identify the true clusters.

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ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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