A study of dynamic knowledge representation based on neural networks

The competitive learning technique is a well-known algorithm used in neural networks, which classifies the input vectors, so that the vectors (samples) belonging to the same class have similar characteristics. Dynamic competitive learning is an unsupervised learning technique, which consists of two additional parts related to conventional competitive learning: a method of generation of new units within a cluster; and a method of generating new clusters. The model is capable for the high-level storage of complex data structures, whose classification include exception handling.