Sentence examples for mean square bounded from inspiring English sources

The purpose of this problem is to design a recursive state estimator such that, for all admissible coupling strength uncertainties and linearized errors of nonlinear functions, the estimation error is mean square bounded and the variance of the estimation error is not more than the prescribed upper bound.

After that, by using the algebraic graph theory and stochastic analysis method, it is proved that the followers can achieve mean square bounded output tracking of the leader while keeping all the states of the closed-loop system bounded in probability.

Let (g:Ilongrightarrow L_{2}) be a mean square bounded function and let (h>0), then the mean square modulus of continuity of g is the function omega g,h)= sup_{|t-t^|leq h}{bigl| g(t -gbigl(t -gbiglbigr| },quad t^bigr I.

Furthermore, based on the derived upper bound of PECMS, further sufficient conditions are provided for mean-square bounded estimate error of the MEKF using the fixed-point theorem.

Two estimation problems considered are the designs for the mean-square bounded estimation error and for the mean-square stochastic version of the suboptimal H∞ estimator, respectively.

Table 6 shows the theoretical values of the mean and mean square stability bounds of SR-NSAF and MSR-NSAF algorithms.

Then, a co-design compensation mechanism is also obtained, which can further guarantee the attacked system is stochastically stable (without the zero-mean Gaussian white noise) or mean square exponentially ultimately bounded (with the zero-mean Gaussian white noise).

We propose the use of posterior Cramér-Rao lower bound (PCRLB) as a mean square error (MSE) bound.

The containment tracking results are obtained in the asymptotic unbiased mean square sense and with bounded error in mean square sense for general linear case and nonlinear case respectively.

Using Itˆo formula and Chebyshev's inequality, it is shown that all the signals in the closed-loop system are bounded in probability, and the error signals are semi-globally uniformly ultimately bounded in mean square or the sense of four-moment.

The design objective is to make the error system uniformly ultimately bounded in mean square.