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Noise is the random Gaussian noise whose zero mean square is 0.2.
(i) The almost sure synchronization control other than synchronization in mean square is investigated.
The calculation method of surface parameter including rigid body displacement, surface focus and root mean square is researched.
In addition, the stability in mean square is developed for the above mentioned stochastic dynamical systems in the G-frame.
The mean square is simply calculated by the division of SS to the corresponding DF (Eq. 13).
The definition of the globally robustly exponentially synchronization in the mean square is given firstly in the following.
It shows that the between-sample mean square is greater than the within-sample mean square, and the F test shows that this difference is highly significant.
The value of the mean squares is calculated by dividing the sum of squares of each variable by their respective degree of freedom.
A parametrization of all linear static output feedback controllers that stabilize a given system of this class in the mean square is presented.
The results show that for baselines of about 80 km, the root mean square is at the level of a few centimetres.
The infit mean square is relatively more affected by unexpected responses closer to item and person measures [ 11].
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