Tag: signal-processing

The average filter is the simplest form of recursive estimation. Despite its simplicity, it provides strong noise reduction and forms the foundation of more advanced filters such as the Kalman filter.

The Kalman filter is an optimal recursive estimator for linear systems, combining system models and noisy measurements through simple matrix operations.

A low pass filter reduces noise while emphasizing recent measurements, overcoming the limitations of uniform averaging in moving average filters.

The moving average filter reduces noise while preserving the dynamic behavior of time-varying signals by averaging only a recent window of measurements.