1. An evolutionary neural network comprising: an input set consisting of at least one input neuron, said input neurons being adapted for receiving an input signal form an external system; an output set consisting of at least one output neuron, said output neurons being adapted for producing an output signal for said external system; an internal network composed of a plurality of internal neurons, each internal neuron being adapted for processing a signal received from at least one of said input neurons or other internal neurons and producing a signal for at least one of said output neurons or other internal neurons; and a plurality of synapses constituting connections between said neurons, each of said synapses having a value of strength that can be adjusted by a learning process; wherein each of said neurons is assigned to a neuron class, the parameter values of which are defined by the genotype of the evolutionary neural network; and each of said synapses are assigned to a respective synapse class, the parameter values of which are also defined by said genotype of the evolutionary neural network; and at reproduction, the genotype of any new neural network is subject to genetic operations; wherein the evolutionary neural network is associated with a neural space, said neural space comprising a plurality of neural layers; each neuron is associated with at least one neural layer and described by a set of topographical parameters with respect to said neural space; wherein at least one of said topographical parameters of at least the internal neurons is encoded in the genotype of the evolutionary neural network in a statistical form.