Abstract
We introduce a novel Genetic Programming (GP)
technique to evolve both the structure and parameters
of adaptive Digital Signal Processing (DSP) algorithms.
This is accomplished by defining a set of node
functions and terminals to implement the basic
operations commonly used in a large class of DSP
algorithms. In addition, we show how Simulated
Annealing may be employed to assist the GP in
optimising the numerical parameters of expression
trees. The concepts are illustrated by using GP to
evolve high performance algorithms for detecting binary
data sequences at the output of a noisy, non-linear
communications channel.
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