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.
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Gacek, A., Pedrycz, W. (2012). ECG Signal Analysis, Classification, and Interpretation: A Framework of Computational Intelligence. In: Gacek, A., Pedrycz, W. (eds) ECG Signal Processing, Classification and Interpretation. Springer, London. https://doi.org/10.1007/978-0-85729-868-3_3
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DOI: https://doi.org/10.1007/978-0-85729-868-3_3
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