A Kernel-Based Method for Modeling Non-harmonic Periodic Phenomena in Bayesian Dynamic Linear Models

@article{Nguyen2019AKM,
  title={A Kernel-Based Method for Modeling Non-harmonic Periodic Phenomena in Bayesian Dynamic Linear Models},
  author={Luong Ha Nguyen and Ianis Gaudot and Shervin Khazaeli and James A. Goulet},
  journal={Frontiers in Built Environment},
  year={2019}
}
Modeling periodic phenomena with accuracy is a key aspect to detect abnormal behaviour in time series for the context of Structural Health Monitoring. Modeling complex non-harmonic periodic pattern currently requires sophisticated techniques and significant computational resources. To overcome these limitations, this paper proposes a novel approach that combines the existing Bayesian Dynamic Linear Models with a kernel-based method for handling periodic patterns in time series. The approach is… 

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