Constraint phase optimization in minimum variance synthetic discriminant functions.
It is shown that proper selection of constraint phases in minimum variance synthetic discriminant functions can further reduce the output variance due to input noise. It is demonstrated with the help of examples that this reduction in variance can range from being negligible to being significant. The exact amount of reduction depends on the constraint magnitudes, training images, and the noise covariance matrix.
Kumar
B V
BV
Bahri
Z
Z
Mahalanobis
A
A