  In addition to ever-present thermal noise, communication and sensor systems
can contain significant amounts of interference with outlier (e.g. impulsive)
characteristics. Such outlier interference (including that caused by nonlinear
signal distortions, e.g. clipping) can be efficiently mitigated in real-time
using intermittently nonlinear filters. Depending on the interference nature
and composition, improvements in the quality of the signal of interest achieved
by such filtering will vary from "no harm" to substantial. In this tutorial, we
explain in detail why the underlying outlier nature of interference often
remains obscured, discussing the many challenges and misconceptions associated
with state-of-art analog and/or digital nonlinear mitigation techniques,
especially when addressing complex practical interference scenarios. We then
focus on the methodology and tools for real-time outlier noise mitigation,
demonstrating how the "excess band" observation of outlier noise enables its
efficient in-band mitigation. We introduce the basic real-time nonlinear
components that are used for outlier noise filtering and provide examples of
their implementation. We further describe complementary nonlinear filtering
arrangements for wide- and narrow-band outlier noise reduction, providing
illustrations of their performance and the effect on channel capacity. Finally,
we outline "effectively analog" digital implementations of these filtering
structures, discuss their broader applications, and comment on the ongoing
development of the platform for their demonstration and testing. To emphasize
the effectiveness and versatility of this approach, in our examples we use
particularly challenging waveforms that severely obscure low-amplitude outlier
noise, such as broadband chirp signals (e.g. used in radar, sonar, and
spread-spectrum communications) and "bursty," high crest factor signals (e.g.
OFDM).
