Hebb and Hopfield

• When used with Hopfield type activation rules, the Hebb learning rule places patterns at attractors

• If a network has n nodes, 0.15n random patterns can be reliably stored by such a system

• For complete retrieval it is typically necessary to present the network with over 90% of the original pattern