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noise-filtering

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The `KalmanFilter` class implements the Kalman Filter algorithm for estimating the state of linear dynamic systems using noisy measurements. The class accepts system matrices, initial state, and covariance, and provides `predict` and `update` methods for state prediction and refinement based on new observations.

  • Updated Apr 25, 2023
  • Python

End-to-end pipeline for hydrometeorological time-series processing and flash-flood modeling with a ML framework. Integrates rain-gauge and river-stage data through advanced preprocessing (with outlier detection & noise filtering) for flood forecasting with classical ML models; performance evaluation and exploratory/statistical analysis of results.

  • Updated Mar 19, 2026
  • Jupyter Notebook

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