Adaptive Resonance Theory ART Networks

More than 50 different types of neural network exist. Certain networks are more efficient in optimization others perform better in data modeling and so forth. According to Basheer (2000) the most popular neural networks today are the Hopfield networks, the Adaptive Resonance Theory (ART) networks, the Kohonen networks, the counter propagation networks, the Radial Basis Function (RBF) networks, the backpropagation networks and recurrent networks. 

D. Wienke and L.M.C. Buydens, Adaptive resonance theory neural networks — the ART of real-time pattern recognition in chemical process monitoring Trends Anal. Chem., 99 (1995) 1-8. 

Domine and co-workers utilized the family of Adaptive Resonance Theory (ART and ART 2-A) based artificial neural networks for unsupervised and supervised pattern recognition (142,143). The simplest ART network is a vec-... 

Neuronal networks are nowadays predominantly applied in classification tasks. Here, three kind of networks are tested First the backpropagation network is used, due to the fact that it is the most robust and common network. The other two networks which are considered within this study have special adapted architectures for classification tasks. The Learning Vector Quantization (LVQ) Network consists of a neuronal structure that represents the LVQ learning strategy. The Fuzzy Adaptive Resonance Theory (Fuzzy-ART) network is a sophisticated network with a very complex structure but a high performance on classification tasks. Overviews on this extensive subject are given in [2] and [6]. 

Neural network learning algorithms BP = Back-Propagation Delta = Delta Rule QP = Quick-Propagation RP = Rprop ART = Adaptive Resonance Theory, CP = Counter-Propagation. 

Wienke, D., Vandenbroek, W., Meissen, W., Buydens, L., Feldhoff, R., Kantimm, T., Huthfehre, T., Quick, L., Winter, F. Cammann, K. (1995) Comparison of an adaptive resonance theory-based neural network (ART- 2A) against other classifiers for rapid sorting of post consumer plastics by remote near-infrared spectroscopic sensing using an InGaAs diode array. Analytica ChimicaActa 317, 1-16. 

D. Wienke and L. Buydens, Trends AnaL Chem., 14, 398 (1995). Adaptive Resonance Theory Based Neural Networks—the ART of Real-Time Pattern Recognition in Chemical Process Monitoring ... 

Wienke, D., et al.. Comparison of an Adaptive Resonance Theory Based on Neural Network (ART-2a) against other Classifiers for Rapid Sorting of Post Consumer Plastics by Remote Near Infrared Spectroscopic Sensing Using an InGaAs Diode Array. AnaZ. Chim. Acta, 1995. 317 1-16. 

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