An average-compress algorithm for the sample mean problem under dynamic time warping
نویسندگان
چکیده
Abstract Computing a sample mean of time series under dynamic warping is NP-hard. Consequently, there an ongoing research effort to devise efficient heuristics. The majority heuristics have been developed for the constrained problem that assumes solution predefined length. In contrast, on unconstrained underdeveloped. this article, we propose generic average-compress (AC) algorithm address problem. alternates between averaging (A-step) and compression (C-step). A-step takes initial guess as input returns approximation mean. Then C-step reduces length approximate solution. compressed serves in next iteration. purpose direct more promising solutions shorter proposed sense any method can be used. Experimental results show AC substantially outperforms current state-of-the-art algorithms averaging.
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ژورنال
عنوان ژورنال: Journal of Global Optimization
سال: 2023
ISSN: ['1573-2916', '0925-5001']
DOI: https://doi.org/10.1007/s10898-023-01294-9