Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/77307 
Year of Publication: 
2000
Series/Report no.: 
Technical Report No. 2000,23
Publisher: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Abstract: 
This paper presents the application of special unsupervised neural networks (self-organizing maps) to different domains, as sleep apnea discovery, protein sequences analysis and tumor classification. An enhancement of the original algorithm, as well as the introduction of several hierachical levels enables the discovery of complex structures as present in this type of applications. Furthermore, an integration of unsupervised neural networks with hidden markov models is proposed.
Subjects: 
Unsupervised Neural Networks
Hidden Markov Models
Sleep Apnea
Protein Sequences
Tumor Classification
Document Type: 
Working Paper

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