Abstract
The family of artificial neural networks based on Adaptive Resonance Theory (ART) forms a collection of distinct mathematical pattern recognition methods. The classification of sensor signals, process data analysis, spectral interpretation, and image analysis are discussed as applications of ART outside and within chemistry. The advantages of ART are considered. They include its use as a built-in detector for outliers, its rapid training speed, self-organizational behaviour, full chemical interpretability, and real-time and on-line applicability. A glossary of terms used in ART is given at the end of the article.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.