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Soft Computing
Erschienen in: Soft Computing 9/2013

01.09.2013 | Methodologies and Application

Description, analysis, and classification of biomedical signals: a computational intelligence approach

verfasst von: Adam Gacek, Witold Pedrycz

Erschienen in: Soft Computing | Ausgabe 9/2013

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Abstract

This study provides a general introduction to the principles, algorithms and practice of computational intelligence (CI) and elaborates on those facets with relation to biomedical signal analysis, especially ECG signals. We discuss the main technologies of computational intelligence (namely, neural networks, fuzzy sets or granular computing, and evolutionary optimization), identify their focal points and stress an overall synergistic character, which ultimately gives rise to the highly symbiotic CI environment. Furthermore, the main advantages and limitations of the CI technologies are discussed. In the sequel, we present CI-oriented constructs in signal modeling, classification, and interpretation. Examples of the CI-based ECG signal processing problems are presented.
Vorheriger Artikel Rough subspace-based clustering ensemble for categorical data
Nächster Artikel Interpretability-based fuzzy decision tree classifier a hybrid of the subtractive clustering and the multi-objective evolutionary algorithm

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Metadaten
Titel
Description, analysis, and classification of biomedical signals: a computational intelligence approach
verfasst von
Adam Gacek
Witold Pedrycz
Publikationsdatum
01.09.2013
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 9/2013
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-012-0967-5

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