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ECG Signal Processing, Classification and Interpretation A Comprehensive Framework of Computational Intelligence /

Electrocardiogram (ECG) signals are among the most important sources of diagnostic information in healthcare so improvements in their analysis may also have telling consequences. Both the underlying signal technology and a burgeoning variety of algorithms and systems developments have proved success...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Gacek, Adam (Editor ), Pedrycz, Witold (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2012.
Edición:1st ed. 2012.
Temas:
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Part I: Introduction
  • Introduction to ECG Signal Processing
  • Fuzzy Sets: A Primer
  • Neural Networks and Neurocomputing
  • Evolutionary and Population-based Optimization
  • Part II: Techniques and Models of Computational Intelligence for ECG Signal Analysis and Classification
  • Neurocomputing in ECG Signal Classification
  • Knowledge-based Representation and Processing of ECG Signals: A Fuzzy Set Approach
  • Evolutionary Optimization of ECG Signal Analysis and Classification
  • Granular Models of ECG Signal Analysis and Their Refinements and Abstractions
  • Hybrid Architectures of ECG Analyzers and Classifiers. Part III: Computational-intelligence-based ECG System Diagnostic, Interpretation and Knowledge Acquisition Architectures
  • Diagnostic ECG Systems and Computational Intelligence: Development Issues
  • Interpretation of ECG Signals: A Systems Approach
  • Knowledge Representation and ECG Diagnostic and Interpretation Systems.