Minimum squared error synthetic discriminant functions

A new synthetic discriminant function (SDF) design approach is presented that yields the best approximation of arbitrary output correlation shapes in the minimum squared error (MSE) sense. We term such filters as MSE-SDFs. Simulation results are presented to illustrate the advantages of MSE-SDFs. Also, we show that MSE-SDFs generalize minimum average correlation energy filters.