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Nonlinear effects, or non-Wiener behavior, have been
observed in several adaptive filtering applications,
such as adaptive equalization of wideband communication
signals contaminated by narrowband interference, adaptive
narrowband noise cancellation, and adaptive linear prediction
of narrowband processes. The nonlinear effects have
been especially prominent when narrowband processes
have been involved, and revealed by performance better
than expected from the conventional Wiener filter for
that scenario. Furthermore, in the adaptive noise-canceling
scenario, almost deterministic semi-periodic dynamic
behavior of the adaptive filter weights has been observed.
In the adaptive equalization and prediction scenarios
the weight behavior is also dynamic, albeit of a different
nature. The dynamic weight behavior associated with
nonlinear effects is shown to be the result of how the
conventional NLMS adaptive filter tracks the equivalent
model for the desired signal.
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