ADAPTIVE RESONANCE THEORY-BASED NEURAL NETWORKS - THE ART OF REAL-TIME PATTERN-RECOGNITION IN CHEMICAL PROCESS MONITORING

The family of artificial neural networks based on Adaptive Resonance T heory (ART) forms a collection of distinct mathematical pattern-recogn ition methods, The classification of sensor signals, process data anal ysis, spectral interpretation, and image analysis are discussed as app lications of ART outside and within chemistry, The advantages of ART a re considered. They include its use as a built-in detector for outlier s, its rapid training speed, self-organizational behaviour, full chemi cal interpretability, and real-time and on-line applicability. A gloss ary of terms used in ART is given at the end of the article.