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Computational Pulse Signal Analysis
Computational Pulse Signal Analysis
Knygos.lt klubas Knygos.lt nariams
209,77 €
-15%
Įprastai
246,79 €
  • Išsiųsime per 12–18 d.d.
This book describes the latest advances in pulse signal analysis and their applications in classification and diagnosis. First, it provides a comprehensive introduction to useful techniques for pulse signal acquisition based on different kinds of pulse sensors together with the optimized acquisition scheme. It then presents a number of preprocessing and feature extraction methods, as well as case studies of the classification methods used. Lastly it discusses some promising directions for the f…
  • Leidėjas:
  • ISBN-10: 9811338353
  • ISBN-13: 9789811338359
  • Formatas: 15.6 x 23.4 x 1.8 cm, minkšti viršeliai
  • Kalba: Anglų

Computational Pulse Signal Analysis (el. knyga) (skaityta knyga) | knygos.lt

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This book describes the latest advances in pulse signal analysis and their applications in classification and diagnosis. First, it provides a comprehensive introduction to useful techniques for pulse signal acquisition based on different kinds of pulse sensors together with the optimized acquisition scheme. It then presents a number of preprocessing and feature extraction methods, as well as case studies of the classification methods used. Lastly it discusses some promising directions for the future study and clinical applications of pulse signal analysis. The book is a valuable resource for researchers, professionals and postgraduate students working in the field of pulse diagnosis, signal processing, pattern recognition and biometrics. It is also useful for those involved in interdisciplinary research.


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  • Autorius: David Zhang
  • Leidėjas:
  • ISBN-10: 9811338353
  • ISBN-13: 9789811338359
  • Formatas: 15.6 x 23.4 x 1.8 cm, minkšti viršeliai
  • Kalba: Anglų

This book describes the latest advances in pulse signal analysis and their applications in classification and diagnosis. First, it provides a comprehensive introduction to useful techniques for pulse signal acquisition based on different kinds of pulse sensors together with the optimized acquisition scheme. It then presents a number of preprocessing and feature extraction methods, as well as case studies of the classification methods used. Lastly it discusses some promising directions for the future study and clinical applications of pulse signal analysis. The book is a valuable resource for researchers, professionals and postgraduate students working in the field of pulse diagnosis, signal processing, pattern recognition and biometrics. It is also useful for those involved in interdisciplinary research.


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