A new neural network architecture is introduced for incremental supervised learning of
recognition categories and multidimensional maps in response to arbitrary sequences of …

Abstract A Fuzzy Adaptive Resonance Theory (ART) model capable of rapid stable learning
of recognition categories in response to arbitrary sequences of analog or binary input …

A neural network model of synchronized oscillator activity in visual cortex is presented in
order to account for recent neurophysiological findings that such synchronization may reflect …

This paper announces a new neural network architecture, called ARTMAP [1], that
autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition …

ABSTRACT A neural network realization of the fuzzy Adaptive Resonance Theory (ART)
algorithm is described. Fuzzy ART is capable of rapid stable learning of recognition …

Abstract Adaptive Resonance Theory(ART) has been used to design a number of massively-
parallel, unsupervised, pattern recognition machines. ART networks learn a set of …

Abstract Development of a machine methodology with ability to generate qualitative
interpretations (QIs) of two-dimensional sensor patterns is described. The approach …

A neural network model of synchronized oscillator activity in visual cortex is presented in
order to account for recent neurophysiological findings that such synchronization may reflect …

ARTMAP is a class of neural network architectures that perform incremental supervised
learning of recognition categories and multidimensional maps in response to input vectors …