Research Article

# Target Detection Using Nonsingular Approximations for a Singular Covariance Matrix

## Table 3

This table shows the time it took to complete the calculation of a dataset.
 “Name” “OWS” “GWS” Original SMT number of rotations SMT after PCA number of rotations Rotations number ratio “OP1_T1_S10” 9 1 3845 1851 2.1 “OP1_T1_S33” 9 1 3794 1831 2.1 “OP1_T1_S100” 9 1 3820 1806 2.1 “OP1_T1_S10” 7 1 2781 1508 1.8 “OP1_T1_S33” 7 1 2769 1498 1.8 “OP1_T1_S100” 7 1 2770 1457 1.9 “OP1_T1_S10” 5 1 1965 1177 1.7 “OP1_T1_S33” 5 1 1969 1203 1.6 “OP1_T1_S100” 5 1 1965 1122 1.8 “OP1_T1_S10” 3 1 1195 442 2.7 “OP1_T1_S33” 3 1 1187 407 2.9 “OP1_T1_S100” 3 1 1201 421 2.9 “OP2_T1_S10” 9 1 2135 839 2.5 “OP2_T1_S33” 9 1 2105 840 2.5 “OP2_T1_S100” 9 1 2095 827 2.5 “OP2_T1_S10” 7 1 1480 647 2.3 “OP2_T1_S33” 7 1 1481 641 2.3 “OP2_T1_S100” 7 1 1464 635 2.3 “OP2_T1_S10” 5 1 961 440 2.2 “OP2_T1_S33” 5 1 962 435 2.2 “OP2_T1_S100” 5 1 960 431 2.2 “OP2_T1_S10” 3 1 556 203 2.7 “OP2_T1_S33” 3 1 555 205 2.7 “OP2_T1_S100” 3 1 552 206 2.7
The smaller the number of rotations, the less time needed for the calculation.

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