Symmetric nonlinear matched filters (SNMFs) involve the transformation
of the signal spectrum and the filter transfer function through
pointwise nonlinearities before they are multiplied in the transform domain.
The resulting system is analogous to a multistage neural network.
The experimental and theoretical results discussed indicate that SNMFs
hold considerable potential to achieve a high power of discrimination and
resolution and large SNR. The statistical analysis of a particular SNMF in
the two-class problem indicates that the performance coefficient of the
SNMF is about four times larger than the performance coefficient of the
classical matched filter. In terms of resolving closeby signals, there seems
to be no limit to the achievable resolution. However, artifacts should be