PCN: the probabilistic convergent network

A new architecture for networks constructed from RAM-based neurons is presented which, whilst retaining learning and generalisation properties possessed by existing RAM-based network architectures, allows for a regular treatment of specialisation and generalisation with the additional property of providing information regarding the relative probability of a given sample pattern being a member of each possible pattern class. The network architecture provides the basis for the development of a pattern recognition system capable of application in a practical environment