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Guimaraes, Gabriela
Urfer, Wolfgang
Year of Publication: 
Series/Report no.: 
Technical Report, SFB 475: Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 2000,23
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.
Unsupervised Neural Networks
Hidden Markov Models
Sleep Apnea
Protein Sequences
Tumor Classification
Document Type: 
Working Paper

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