Order of Search in Fuzzy ART and Fuzzy ARTMAP: Effect of the Choice Parameter

This paper focuses on two ART architectures, the Fuzzy ART and the Fuzzy ARTMAP. Fuzzy ART is a pattern clustering machine, while Fuzzy ARTMAP is a pattern classification machine. Our study concentrates on the order according to which categories in Fuzzy ART, or the ART(a) model of Fuzzy ARTMAP are chosen. Our work provides a geometrical, and clearer understanding of why, and in what order, these categories are chosen for various ranges of the choice parameter of the Fuzzy ART module. This understanding serves as a powerful tool in developing properties of learning pertaining to these neural network architectures; to strengthen this argument, it is worth mentioning that the order according to which categories are chosen in ART 1 and ARTMAP provided a valuable tool in proving important properties about these architectures. Copyright 1996 Elsevier Science Ltd.

[1]  Stephen Grossberg,et al.  Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system , 1991, Neural Networks.

[2]  Stephen Grossberg,et al.  Art 2: Self-Organization Of Stable Category Recognition Codes For Analog Input Patterns , 1988, Other Conferences.

[3]  Michael Georgiopoulos,et al.  Properties of learning related to pattern diversity in ART1 , 1991, Neural Networks.

[4]  Stephen Grossberg,et al.  A massively parallel architecture for a self-organizing neural pattern recognition machine , 1988, Comput. Vis. Graph. Image Process..

[5]  Gail A. Carpenter,et al.  Fuzzy ART Choice Functions , 1993 .

[6]  Stephen Grossberg,et al.  ARTMAP: supervised real-time learning and classification of nonstationary data by a self-organizing neural network , 1991, [1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering.

[7]  Michael Georgiopoulos,et al.  Fuzzy ART properties , 1995, Neural Networks.

[8]  Thomas P. Caudell,et al.  A neural architecture for pattern sequence verification through inferencing , 1993, IEEE Trans. Neural Networks.

[9]  Michael Georgiopoulos,et al.  Convergence Properties of Learning in ART1 , 1990, Neural Computation.

[10]  B. Moore,et al.  ART1 and pattern clustering , 1989 .

[11]  Stephen Grossberg,et al.  Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps , 1992, IEEE Trans. Neural Networks.

[12]  Michael Georgiopoulos,et al.  The N-N-N conjecture in ART1 , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

[13]  Anil K. Jain,et al.  Clustering techniques: The user's dilemma , 1976, Pattern Recognit..

[14]  Michael Georgiopoulos,et al.  The N-N-N conjecture in ART1 , 1992, Neural Networks.

[15]  Stephen Grossberg,et al.  ART 3: Hierarchical search using chemical transmitters in self-organizing pattern recognition architectures , 1990, Neural Networks.

[16]  Michael Georgiopoulos,et al.  Properties of learning in ARTMAP , 1994, Neural Networks.