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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2130, Issue , 2001, Pages 464-469

Combining the self-organizing map and k-Means clustering for on-line classification of sensor data

(1) Van Laerhoven, Kristof a

a Starlab NV (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER HARDWARE; CONFORMAL MAPPING; HUMAN COMPUTER INTERACTION; NEURAL NETWORKS; SELF ORGANIZING MAPS;

ADAPTIVE APPROACH; CONTEXT DETECTION; HARDWARE SENSORS; K-MEANS CLUSTERING; KOHONEN SELF-ORGANIZING MAPS; NEAR-REAL TIME; NOISY SENSORS; ON-LINE CLASSIFICATION;

CLASSIFICATION (OF INFORMATION);

EID: 84958967653 PISSN: 03029743 EISSN: 16113349 Source Type: Book Series
DOI: 10.1007/3-540-44668-0_65 Document Type: Conference Paper

Times cited : (56)

References (8)

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2
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3
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- Kohonen, T.¹

5
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- Springer-Verlag
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- Von Der Malsburg¹

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- Grossberg, S.¹

7
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- Limitations of Self-organizing Maps for Vector Quantization and Multidimensional Scaling
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- Flexer, A. Limitations of Self-organizing Maps for Vector Quantization and Multidimensional Scaling, in Mozer M.C., et al.(eds.), Advances in Neural Information Processing Systems 9, MIT Press/Bradford Books, (1997) 445-451
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- Flexer, A.¹

8
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- On convergence of k-means and partitions with minimum average variance
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