Sentence examples for minimum variance direction from inspiring English sources

The minimum variance direction provides the propagation direction of the wave.

An attempt was made to obtain the direction of the wave number vector using minimum variance analysis, but the ratio of the intermediate to minimum variance was not large enough to obtain the minimum variance direction with a good accuracy.

Figure 5 shows an example of the direction of the minimum variance and the hodogram for an 8-s period from 5 24 0 to 5 24 8, during which the ratio of medium to minimum variance was 4 and the minimum variance direction was calculated to be (0.83, 0.48, –0.28) in SSE coordinates.

The maximum and minimum variance directions in the wavevector spectrum show an offset angle from the mean magnetic field by 76.9(^{circ }).

The essence of the analysis is to extract the information on the principal axis (or the maximum and minimum variance directions) using the spectral moments, and to interpret the spectra in the frame of random sweeping model.

Figure 3 presents the result of minimum variance analysis (Sonnerup and Cahill 1967) for the time interval from 11 00 to 23:10 UT on 17 March with 1-min averagedatata (14:10–16:50 UT data being excluded), where B1, B2 and B3 denote the magnetic field components in the maximum, intermediate and minimum variance directions, respectively.

As shown in Additional file 1: Figure S1, Additional file 2: Figure S2 and Additional file 4: Figure S4, Additional file 5: Figure S5, the magnetic field jumps across the shocks are often linearly polarized in the GSM Y or Z directions; thus, the median and minimum variance directions are not determined precisely.

1995) with a one-dimensional spectral index of (-5/3), begin{aligned} E k_1, k_2) propto left[ frac{lambda _1}{lambda _2} (k_1)^2 + (k_2)^2 right] ^{-5/6} end{aligned} (16 in the domain spanning the wavevector components in maximum and minimum variance directions, (k_1) and (k_2), respectively.

In the present investigation, we use the technique developed by McPherron et al. (1972) in which the diagonalization of the real part of the power spectral density matrix gives the three eigenvectors (ζ 1,ζ 2,ζ 3) and corresponding eigenvalues (λ 1,λ 2,λ 3) for maximum, intermediate, and minimum variance directions, respectively.

The adaptive controller is composed of an identifier and the minimum variance direct control.

Further suitable methods are the coherence-based SDR estimator proposed in [18] or a linearly constrained minimum variance (LCMV) beamformer placing nulls in the direction of direct sound sources while extracting the ambient sound [19].