Abstract
The problem of source identification involves
correctly classifying an incoming signal into a
category that identifies the signal's source. The
problem is difficult because information is not
provided concerning each source's distinguishing
characteristics and because successive signals from the
same source differ. The source identification problem
can be made more difficult by dynamically changing the
repertoire of sources while the problem is being
solved. We used genetic programming to evolve both the
topology and the sizing (numerical values) for each
component of an analog electrical circuit that can
correctly classify an incoming analog electrical signal
into three categories. Then, the repertoire of sources
was dynamically changed by adding a new source during
the run. The paper describes how the
architecture-altering operations enabled genetic
programming to adapt, during the run, to the changed
environment. Specifically, a three-way source
identification circuit was evolved and then adapted
into a four-way classifier, during the run, thereby
successfully handling the additional new source.
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