text: Different strategies and configurations for improving the MLP performance have been proposed such as: the learning data normalization, the use of Gaussian activation functions (GMLP) [57], the dynamic addition of neurons, the evolvable MLP with GA [1], the modular MLP (that is the decomposition of N -class MLP into (N(n− 1)/2) binary MLPs or into N binary MLPs of type one-against-all) [48, 55] and so on.