Estimators for relative errors in A-norm and their extension to errors in l2 norm are presented with numerical results. Estimating the relative error from the residue in an iterative solution is required for efficient solution of a large problem with even a moderately high condition. Specifically,...
(SNR) from the mean expressed in standard deviations. The intent is to derive an indicator for multipath. The SNR data correspond to the satellites shown in FIG. 3A. FIG. 3C illustrates the search ratio, i.e., the ratio of the square of the smallest residual norm found by the search,...
First, the norm of a vector will simply be denoted by the non-bold variable, such that = ‖‖ . Second, the pro- jection of a vector along a coordinate axes will be denoted by a subscript such that x = T x̂. Spaceflight dynamics' primary driving force is from a gravitational ...
In Fig. 3, we show mapping (L2 norm) from the original 15,154-dimensional feature space to the RDP. This produced eight misclassifications in the TS and nine in the VS (Fig. 3A). After feature space reduction, two different 5-dimensional feature sets, with M/Z value positions 7-12-...
(x, y) represents the pixel coordinates in a panorama, Iμ is the arithmetic mean pixel value of the image, Iωhc(x, y) is the Gaussian blurred version of the original image (required to eliminate fine texture details, noise, and coding artifacts), and represents the L2 norm for ...
The most widely used robust filter adopts a Huber kernel function that combines minimum l1 and l2 norm estimation techniques [30]. Gaussian kernel function is another robust kernel function, namely, the maximum correntropy criterion (MCC). Since the weight function is smaller for the same residual...
constants import rhi_cmap_smooth, norm1, font2 __all__ = ['Section'] 4 changes: 2 additions & 2 deletions 4 cinrad/visualize/shapepatch.py Original file line numberDiff line numberDiff line change @@ -8,8 +8,8 @@ from matplotlib.path import Path from matplotlib.patches import Path...