Evolution of computational efficiency in visual processing

Feedforward networks are used to carry out a simple classification task: determining the position and identity of simple geometrical figures. Earlier work proposes computational efficiency as a rationale for the modular structure of the best of such networks. Genetic algorithms are used to optimise network structure and test this proposition in greater depth. Appropriate fitness functions for network performance give rise to a modular network structure and improved convergence and accuracy