Sentence examples for estimation of the phase from inspiring English sources
With the estimation of the phase's permeabilities, it is therefore possible to estimate the possible relative permeability for each phase and the percentage each phase contribution to flow at one point analysis; hence at several point, the relative k can be generated.
The aims of this processing are to get an accurate estimation of the phase and to use it to get centimeter precise position estimates every millisecond.
Data analyses, such as an estimation of the phase speed of atmospheric waves, also suffer from the same difficulty.
The estimation of the phase trajectory involves the inversion of the matrix, which depends on the pilot symbol positions.
But a reliable estimation of the phase differences is only possible in speech active periods and furthermore only for that frequencies where speech is present.
Also, parameters of circular fringes can be retrieved with the Fourier transform via the estimation of the phase and its derivatives [9].
In the MSNWF-DOA system, the optimal estimation of the phase-shifted reference signal ( {e}^{j{phi}_k}{mathbf{r}}_k ) in the minimum mean square error sense can be obtained at the output of the adaptive beamformer B, where the adaptive beamforming weights obtained from the adaptive beamformer A with the MSNWF structure were used.
Thus, ( {widehat{mathbf{r}}}_k ) is an optimal estimation of the phase-shifted reference signal ( {e}^{j{phi}_k}{mathbf{r}}_k ) in the MMSE sense, which can be written as {widehat{mathbf{r}}}_k={e}^{j{phi}_k}{mathbf{r}}_k+mathbf{N} (26).
The estimation of the phases is sequential.
We provide only the equations used for the estimation of the map phase's execution time but their applicability for the other two phases is trivial.
For each parameter, correlations for eleven conditions are displayed: the first correlation is for the trajectories predicted by concatenative synthesis using multirepresented diphones (see text); the second correlation is for trajectories predicted by HMM using acoustic boundaries; the rest of the data give results obtained after the successive iteration of the estimations of the phasing model.
