Sentence examples for by the estimation algorithm from inspiring English sources

All the parameters θ (parameter vector of the modeled part) and θ ′ (parameter vector of the unmodeled part) are assumed to be unknown in the most general framework, the first one being estimated by the estimation algorithm.

It is easy for us to obtain a S αS distribution sequence based on the parameter α e, X k ∼(α e,0,1,0), α e is estimated by the estimation algorithm presented in Section 2, which is same to the practical noise sequence.

It can be seen clearly that the use of the sequential estimation algorithm enhances the performance significantly, even if only a single LOS path is considered by the estimation algorithm.

These analyses show that, in some cases, differences in tuning between STRFs derived from responses to song and ml noise stimuli can be explained in terms of biases introduced by the estimation algorithm, rather than actual tuning nonlinearities [2].

We asked whether and how much of the tuning differences we observe between song and ml noise STRFs (see Figs. 5, 6 and 7) can be explained in terms of biases introduced by the estimation algorithm.

In contrast, for the example shown in Figure 8C, differences between Kn and Ks can be explained by biases introduced by the estimation algorithm (that is, Kns is significantly more similar to Ks than to Kn, even though the responses used to compute Kns were originally generated from Kn).

The divergence in the decomposition between this model and UC-CN, even if the additional mixture appears not to be relevant, could be explained by the sensitivity of the estimation algorithm.

By doing so, regardless of the estimation algorithm to be used, a guaranteed transient performance and final tracking accuracy can be achieved even in the presence of disturbances and uncertain nonlinearities, a desirable feature in applications.

We show that the energy required for processing the preamble signal by executing the estimation algorithms dominates the total energy consumed by the channel estimation process.

The illustration examples in the paper are obtained using a freely available MATLAB toolbox developed by the authors, which implements the estimation algorithms described.

The performance of the estimation algorithms is illustrated by simulation studies and measurement data, showing excellent convergence results.