  Traditionally, signal classification is a process in which previous knowledge
of the signals is needed. Human experts decide which features are extracted
from the signals, and used as inputs to the classification system. This
requirement can make significant unknown information of the signal be missed by
the experts and not be included in the features. This paper proposes a new
method that automatically analyses the signals and extracts the features
without any human participation. Therefore, there is no need for previous
knowledge about the signals to be classified. The proposed method is based on
Genetic Programming and, in order to test this method, it has been applied to a
well-known EEG database related to epilepsy, a disease suffered by millions of
people. As the results section shows, high accuracies in classification are
obtained
