This paper describes in a unified mathematical framework a class of associative memory neural networks (AMN), that have very fast learning rates, local generalisation, parallel implementation, and guaranteed convergence to the mean squared error, making them appropriate for applications such as intelligent control and on-line modelling of nonlinear dynamical processes.