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The deterministic autoregressive moving average (DARMA) model with auxiliary input is introduced to cope with any disturbances of the system.
Separating the model into a translational subsystem and a rotational subsystem, an intermediary control input is introduced to track a desired velocity and extract desired orientations.
The road input is introduced by a cam and a roller follower mechanism driven by 1.12 kW single phase induction motor with speed reduction assembly.
As such an input is introduced and increased, phase-lag is seen to decrease and approach zero.
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Then, the auxiliary variables related to the system state and input are introduced to derive an augmented error system that includes future information on the reference signal.
We therefore expected that if further sensory input was introduced subsequent to illusion onset, then it would have a tendency to be incorporated into the illusion rather than work against and perhaps extinguish the illusion.
The step-pulse-shaped input was introduced for cross-validation of the model since this input was not used for building the model.
Borrowing strength, i.e. the optimal estimation of experiment-specific unknown forward model inputs, is introduced as a means for combining information in inverse problems.
A new filter structure known as the NARMAX model (Non-linear Auto Regressive Moving Average model with eXogenous inputs) is introduced as a basis for the design of a class of non-linear filters which can be used for noise cancellation.
As soon as one of the inputs is introduced (A, giving an input of 1 after t≈60 hours), the correct output must be "0".
Due to the presence of disturbances, auxiliary control inputs are introduced in the state observer to attenuate their effects.
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CEO of Professional Science Editing for Scientists @ prosciediting.com