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Neuro-Fuzzy Pattern Recognition

Authors: H Bunke; A Kandel;

Neuro-Fuzzy Pattern Recognition

Abstract

Methodology: simultaneous feature analysis and system identification in a neuro-fuzzy framework, N.R. Pal and D. Chakraborty neuro-fuzzy model for unsupervised feature extraction with real-life applications, R.K. De et al a computational-intelligence-based approach to decision support, M.B. Gorzalczany clustering problem using fuzzy C-means algorithms and unsupervised neural networks, J.-S. Lin automatic training of min-max classifiers, A. Rizzi granular computing in pattern recognition, W. Pedrycz and G. Vukovich ART-based model set for pattern recognition - FasArt family, G.I. Sainz Palmero et al. Applications: a methodology and a system for adaptive speech recognition in a noisy environment based on adaptive noise cancellation and evolving fuzzy neural networks, N. Kasabov and G. Iliev neural versus heuristic development of Choquet fuzzy integral fusion algorithms for land mine detection, P.D. Gader et al automatic segmentation of multi-spectral MR brain images using a neuro-fuzzy algorithm, S.Y. Lee et al vision-based neuro-fuzzy control of autonomous lane following vehicle, Y.-J. Ryoo.

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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Top 10%
Average
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