Sentence examples for variance directions from inspiring English sources

Using data collected by the AMPTE-UKS satellite on 21st September , 1984 this paper investigates the nature of these waves using the variance analysis technique to determine the polarisation and maximum/minimum variance directions.

The results show that the individual oscillations do indeed posses non-planar characteristics and the variation in the maximum/minimum variance directions indicates that these oscillations are in fact 3D structures propagating with the plasma rather than a 2D plane wave.

For example, the principal component analysis (PCA) can preserve the large variance directions [20].

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.

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.

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

Gu et al. computed fixed weights for kernels by projecting them in the maximum variance direction [20].

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 first principal component (t[1]) best approximates the data in a least squares sense and represents the maximum variance direction in the data.