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In this paper, we study the influence of perturbations in a hybrid digital-optical correlator that uses images obtained from CCD camera and rotation-invariant maximum average correlation height filter.
In this paper, we implement a wavelet-modified maximum average correlation height (WaveMACH) filter for recognition of 0 360° out-of-plane rotated targets employing hybrid digital optical correlator architecture.
In this paper, we therefore demonstrate the use of the wavelet-modified maximum average correlation height (WaveMACH) filter for automatic target recognition applications in both the visible and infrared (IR) spectral bands.
The Maximum Average Correlation Height filter designed by Grey Wolf Optimizer obtained the best performance under homogeneous illumination and facial expressions, while the Unconstrained Nonlinear Composite Filter designed by either Grey Wolf Optimizer or (1+1 -Evolution Strategy obtained the best performance under variable illumination.
For a typical 12-min window (Fig. 12), in which we might hope for perfect correlation between stations separated ~ 50 m, we found a maximum average correlation coefficient of 0.98 between our two quietest coils (Zonge ANT4/EMI BFig (Fig. 12b), and only slightly lower average values for cross-correlations of these two sensors with QFido3 (0.94 and 0.92; Fig. 12c, d).
Typically, choosing the maximum average correlation across sessions requires a multiple comparison correction (e.g., Bonferroni).
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The JMA hypocenter and the point of maximum averaged cross-correlation of 0.53 (cross) are shown in the top figure for 3 s (i.e., τ = 0 s) and the middle figure for 7 s (τ = 4 s).
The three sequences with the maximum average distance (i.e., minimum correlation) are shown in Figures 5 and 6.
The maximum average absolute error when using these correlations varies from approximately 32 to 94%%, which indicates that these predictions are often unreliable.
ANN predictions demonstrate us a good statistical performance with the average correlation coefficients of 1.00453 and maximum relative error of 2.32%.
Hence, it is clear from (32) that the minimum outage probability and maximum average SLR transmit beamformer require only the knowledge of correlation matrices and average channel power gains.
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