Dynamics of neural networks with restricted-range connections

The author analyses the neural networks in which the connection range scales sublinearly with the network diameter. Combining this with randomly sparse connectivity leads to fully functional networks with electronically or biologically realisable wiring requirements. Evolution equations for semi-local measures of similarity to the exemplars are derived. Their solutions are analysed to study the process of pattern reconstruction