Nonlinear matched filtering II

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 carefully monitored.