CALM networks: a modular approach to supervised and unsupervised learning

The authors discuss some problems in learning networks. They propose a new learning procedure, CALM (Categorizing And Learning Module). CALM uses pairs of excitatory representation nodes and inhibitory veto nodes, bound together in a modular structure with an arousal node. Learning in the module is enhanced by a nonspecific external node connected to the arousal node. The system is capable of both supervised and unsupervised learning and can both discriminate and generalize across similar patterns. A system constructed out of several CALM modules is shown to learn the XOR relationship with supervised and unsupervised presentation. It also models list recall and word completion memory tasks and can learn, unsupervised, handwritten digits and recognize them with unknown authors.<<ETX>>