Skip to main content

Adaptive Resonance Theory

  • Chapter
  • First Online:
Artificial Neural Networks

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 931))

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • G.A. Carpenter and S. Grossberg (1987a) A massively parallel architecture for a self-organizing neural pattern recognition machine. Computer vision, graphics, and image processing, Vol. 37, 54–115.

    Google Scholar 

  • G.A. Carpenter and S. Grossberg (1987b) ART 2: self-organization of stable category recognition codes for analog input patterns. Applied Optics, Vol. 26, 4919–4930.

    Google Scholar 

  • G.A. Carpenter and S. Grossberg (1990) ART 3: Hierarchical search using chemical transmitters in self-organizing pattern recognition architectures. Neural Networks, Vol. 3, 129–152.

    Article  Google Scholar 

  • G.A. Carpenter, S. Grossberg and J.H. Reynolds (1991) ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network. Neural Networks, Vol. 4, 565–588.

    Article  Google Scholar 

  • G.A. Carpenter, S. Grossberg and D.B. Rosen (1991a) ART2-A: An adaptive resonance algorithm for rapid category learning and recognition. Neural Networks, Vol. 4, 493–504.

    Article  Google Scholar 

  • G.A. Carpenter, S. Grossberg and D.B. Rosen (1991b) Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system. Neural Networks, Vol. 4, 759–771.

    Article  Google Scholar 

  • G.A. Carpenter, S. Grossberg, N. Markuzon, J.H. Reynolds and D.B. Rosen(1992) Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Transactions on Neural Networks, Vol. 3, 698–713.

    Article  Google Scholar 

  • T.P. Caudell, S.D.G. Smith, R. Escobedo and M. Anderson (1994) NIRS: Large scale ART-1 neural architectures for engineering design retrieval. Neural Networks, Vol. 7, 1339–1350.

    Article  Google Scholar 

  • M. Georgiopoulos, G.L. Heileman and J. Huang (1990) Convergence properties of learning in ART1. Neural Computation, Vol. 2, 502–509.

    Google Scholar 

  • M. Georgiopoulos, G.L. Heileman and J. Huang (1991) Properties of learning in ART1. Neural Networks, Vol. 4, 751–757.

    Article  Google Scholar 

  • M. Georgiopoulos, G.L. Heileman and J. Huang (1992) The N-N-N Conjecture in ART1. Neural Networks, Vol. 5, 745–753.

    Article  Google Scholar 

  • M. Georgiopoulos, J. Huang and G.L. Heileman (1994) Properties of learning in ARTMAP. Neural Networks, Vol. 7, 495–506.

    Article  Google Scholar 

  • S. Grossberg (1973) Contour enhancement, short term memory, and constancies in reverberating neural networks. Studies in Applied Mathematics, Vol. LII, 213–257.

    Google Scholar 

  • S. Grossberg (ed.) (1982) Studies of mind and brain: neural principles of learning, perception, development, cognition, and motor control. Boston: Reidel Press.

    Google Scholar 

  • S. Grossberg (ed.) (1986) The adaptive brain I: Cognition, learning, reinforcement, and rhythm. Elsevier/North-Holland, Amsterdam.

    Google Scholar 

  • S. Grossberg (ed.) (1987a) The adaptive brain II: Vision, speech, language, and motor control. Elsevier/North-Holland, Amsterdam.

    Google Scholar 

  • S. Grossberg (1987b) Competitive learning: From interactive activation to adaptive resonance. Cognitive Science, Vol. 11, 23–63.

    Article  Google Scholar 

  • S. Grossberg (1987c) Nonlinear neural networks: principles, mechanisms, and architectures. Neural Networks, Vol. 1, 17–61.

    Article  Google Scholar 

  • B. Moore (1989) ART1 and pattern clustering. In D.S. Touretzky, G. Hinton and T. Sejnowski (Eds.), Proceedings of the 1988 Connectionist Models Summer School Morgan Kaufmann, San Mateo, CA, 174–185.

    Google Scholar 

  • P.K. Simpson (1989) Artificial Neural Systems: Foundations, Paradigms, Applications, and Implementations. Pergamon Press, New York, NY.

    Google Scholar 

  • C.C. Tapang (1989) An alternative matching mechanism: Getting rid of attentional gain control and its consequent 2/3 rule in ART-1. Technical Report, Syntonic Systems, Inc.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

P. J. Braspenning F. Thuijsman A. J. M. M. Weijters

Rights and permissions

Reprints and permissions

Copyright information

© 1995 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Postma, E.O., Hudson, P.T.W. (1995). Adaptive Resonance Theory. In: Braspenning, P.J., Thuijsman, F., Weijters, A.J.M.M. (eds) Artificial Neural Networks. Lecture Notes in Computer Science, vol 931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027025

Download citation

  • DOI: https://doi.org/10.1007/BFb0027025

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-59488-8

  • Online ISBN: 978-3-540-49283-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics