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It is noted that the improvement in the fit to speed is of particular interest in applications of route guidance and ATIS, since a greater accuracy in speed estimation is expected to translate to better estimates of travel times.
For the along-track speed estimation, the two trains detected in the Trenton area (Figure 8) have the along-track speed estimates of m/s and m/s for train 1 and train 2, respectively.
Simulation of downstream speed estimation using populations of speed-tuned units showed that peak (winner take all) readout provided more precise speed estimates than centroid (vector average) readout.
Several methods for CME speed estimation are discussed.
An induction motor speed estimation strategy is presented in this chapter.
The rotor speed estimation is performed using a model reference adaptive system (MRAS).
A stator resistance adaptation scheme for accurate speed estimation at low speeds is derived.
The usage of position sensor simplifies the model and improves the accuracy of speed estimation.
And ANN model can be used for speed estimation with reasonable accuracy.
The wind speed estimation is realized by a nonlinear input output mapping extreme learning machine (ELM).
The rotor position and speed estimation method is based on a modified phase-locked-loop (MPLL).
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