An algebraic method for constructing stable and consistent autoregressive filters

@article{Harlim2015AnAM,
  title={An algebraic method for constructing stable and consistent autoregressive filters},
  author={J. Harlim and H. Hong and J. L. Robbins},
  journal={J. Comput. Phys.},
  year={2015},
  volume={283},
  pages={241-257}
}
In this paper, we introduce an algebraic method to construct stable and consistent univariate autoregressive (AR) models of low order for filtering and predicting nonlinear turbulent signals with memory depth. By stable, we refer to the classical stability condition for the AR model. By consistent, we refer to the classical consistency constraints of Adams-Bashforth methods of order-two. One attractive feature of this algebraic method is that the model parameters can be obtained without… Expand
Forecasting turbulent modes with nonparametric diffusion models: Learning from noisy data

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