This thesis presents a modular strategy towards the implementation and application of an artificial neural network (ANN) paradigm called the Self-Organising Map (SOM). This modular strategy was derived as an approach towards developing an implementable and scaleable ANN system. The design of these modules, called Modular Maps, is presented along with details of suitable implementation technologies. Different connection schemes for combining modules are investigated and their effects discussed. Comparisons of the Modular Map and a unitary SOM system are made. These comparisons include consideration of implementation, training times and performance. The differences between the two systems are then further explored with the aid of two application domains, human face recognition and ground anchorage integrity testing.