Evolutionary wavelet bases in signal spaces

Abstract

We introduce a test environment based on the optimization of signals approximated in function spaces in order to compare the performance of different evolutionary algorithms. An evolutionary algorithm to optimize signal representations by adaptively choosing a basis depending on the signal is presented. We show how evolutionary algorithms can be exploited to search larger waveform dictionaries for best basis selection than those considered in current standard approaches.