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Whales optimization (WO) algorithm, which has recently been introduced in the literature, is used to find the optimal filter solutions.
The great majority of the existing hybrid active power filter solutions is normally focused in 3ϕ systems and, in general, concentrates its domain of application in specific loads with deterministic behavior.
The noise parameterization of the Kalman filter solutions can be found in Table 1.
Primarily, the Kalman filter solutions were compared with the ones obtained from classical least squares adjustments.
As seen in Fig. 1, this gives more smoothed time series compared to the forward and backward Kalman filter solutions.
However, all these methods rely on the assumption that the background surface can be modeled as additive white Gaussian noise, and this assumption leads to matched filter solutions.
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The matlab program also plots the exact filter solution as well as the scaled 24-bit approximation.
The matlab program also plots the exact filter solution as well as the scaled 16-bit approximation.
Particle filter solution of state estimation for stochastic nonlinear system is addressed.
In the paper, the single-input multiple-output (SIMO) universal filter solution employing three UCC elements is also shown.
VIE_KALMAN: This is the newly implemented Kalman filter solution, which is an alternative to VIE_LSM.
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