Evolutionary Signal Processing: A Preliminary Study

The notion of Evolutionary Signal Processing in temporal and ‘spatial’ domains is introduced both theoretically and experimentally. Analytical results from quantitative genetics suggest that in a sinusoidally fluctuating fitness environment, the population mean phenotype tracks the optimum phenotype with a well defined attenuation and phase lag. I show that for the continuous model of (Lande, 1996) [1], evolution acts as a low pass analogue filter and for the discrete, non-overlapping generational model of (Charlesworth, 1993) [2] evolution acts as a band pass nonrecursive digital filter. Results from a genetic algorithm experiment illustrate that these theoretical biology/signal processing models are applicable in the evolutionary computation domain. In addition to the filtering of continuous signals, evolutionary operators that are capable of transforming evaluation and fitness landscapes are likened to spatial image processing filters.