A Generalization of Hebbian Learning in Perceptual and Conceptual Categorization
Harry E. Foundalis, Maricarmen Martínez · 2007
An algorithm for unsupervised competitive learning is presented that, at first sight, appears as a straightforward implementation of Hebbian learning. The algorithm is then generalized in a way that preserves its basic properties but facilitates its use in completely different domains, thus rendering Hebbian learning a special case of its range of applications. The algorithm is not a neural network application: it works not at the neural but at the conceptual level, although it borrows ideas from neural networks. Its performance and effectiveness are briefly examined.