Abstract
Adaptive Resonance is primarily a theory that learning is regulated by resonance phenomena in neural circuits. Diffusion maps are a class of kernel methods on edge-weighted graphs. While either of these approaches have demonstrated success in image analysis, their combination is particularly effective. These techniques are reviewed and some example applications are given.
Recommended Citation
D. C. Wunsch et al., "Adaptive Resonance Theory and Diffusion Maps for Clustering Applications in Pattern Analysis," Donald C. Wunsch, Stephen Damelin, and Rui Xu, Jan 2014.
Meeting Name
Model Reduction Across Disciplines (2014: Aug. 19-22, Leicester, United Kingdom)
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Center for High Performance Computing Research
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2014 Donald C. Wunsch, Stephen Damelin, and Rui Xu, All rights reserved.
Publication Date
01 Jan 2014
Included in
Electrical and Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons
Comments
Invited Opening Keynote