CobART: Correlation Based Adaptive Resonance Theory

Date

2009-06-26

Author

YAVAŞ, mustafa
Alpaslan, Ferda Nur

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This paper introduces a new type of ART 2 network that performs satisfactory categorization for a domain where the patterns are constructed from consecutive analog inputs. The main contribution relies on the correlation analysis methods used for category-matching. The resulting network model is named as Correlation Based Adaptive Resonance Theory (CobART). Correlation waveform analysis and Euclidian distance methods are used to elicit correlation between the learned categories and the data fed to the network.

Subject Keywords

Pattern classification, Correlation analysis, Adaptive resonance theory

URI

https://hdl.handle.net/11511/33295

DOI

https://doi.org/10.1109/med.2009.5164632

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

m. YAVAŞ and F. N. Alpaslan, “CobART: Correlation Based Adaptive Resonance Theory,” 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/33295.