Evolving signal processing algorithms by genetic programming

We introduce a novel genetic programming (GP) technique to evolve both the structure and parameters of adaptive digital signal processing 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, nonlinear communications channel