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ECG Signal Analysis, Classification, and Interpretation: A Framework of Computational Intelligence

  • Adam Gacek
  • Witold Pedrycz
Chapter

Abstract

The study provides a general introduction to the principles, algorithms, and practice of Computational Intelligence (CI) and elaborates on those facets in relation with the ECG signal analysis. We discuss the main technologies of Computational Intelligence (namely, neural networks, fuzzy sets, 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. The design of information granules is elaborated on; their design realized on a basis of numeric data as well as pieces of domain knowledge is considered. Examples of the CI-based ECG signal processing problems are presented.

Keywords

Membership Grade Information Granule Granular Computing Partition Matrix Information Granularity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  1. 1.Institute of Medical Technology and EquipmentZabrzePoland
  2. 2.Department of Electrical & Computer EngineeringUniversity of AlbertaEdmontonCanada
  3. 3.Systems Research Institute Polish Academy of SciencesWarsawPoland

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