AI RESEARCH
Univariate Channel Fusion for Multivariate Time Series Classification
arXiv CS.LG
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ArXi:2604.16119v1 Announce Type: new Multivariate time series classification (MTSC) plays a crucial role in various domains, including biomedical signal analysis and motion monitoring. However, existing approaches, particularly deep learning models, often require high computational resources, making them unsuitable for real-time applications or deployment on low-cost hardware, such as IoT devices and wearable systems. In this paper, we propose the Univariate Channel Fusion (UCF) method to deal with MTSC efficiently.