Sentence examples similar to mean convergence speed from inspiring English sources

where → P means convergence in probability.

This means that the convergence speed is slow and it takes many time slots to converge to the convergence point when the state estimator has no priori information of y(t) at time slot t.

This means that the convergence speed of shuffled decoding in this case is one half.

Figure 5 shows the convergence speed and mean square error of the estimated target position and the true position for different percentages of informed bees in the swarm.

For convergence speed we mean the number of evaluations needed to cross this threshold, and these values are reported in Table 2.

The proposed structure adaptation algorithm maintains a trade-off between the mean square error and convergence speed.

With simulations using random interleavers, we observe the mean degradation on the convergence speed implied by the propagation time for replica shuffled decoding (Figure 6) and for butterfly shuffled decoding (Figure 7).

Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations.

The best performance of the ANN in terms of the mean squared error (MSE) and the convergence speed was achieved when it was initialized and trained using the Nguyen Widrow and Levenberg Marquardt back-propagation algorithms, respectively.

More specifically, we aim to compare mean square error performance and the convergence speed of the aforementioned estimators.

In particular, we propose the asymptotic and per-step (mean square) convergence factors as measures of the convergence speed and derive the exact value for the per-step (mean square) convergence factor.