Titlebook: Computational Pulse Signal Analysis; David Zhang,Wangmeng Zuo,Peng Wang Book 2018 Springer Nature Singapore Pte Ltd. 2018 Computational Pu

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Book 2018ensive 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. Lastl

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Loss Functions and Their Risks,logy to make pulse diagnosis more objective. In this chapter, we will give an overview of computational pulse diagnosis. Firstly, the principle of pulse diagnosis and the traditional pulse diagnosis were introduced, and then the main concept of and the four stages of computational pulse diagnosis were introduced.

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https://doi.org/10.1007/978-3-319-41063-0P kernel, then embed them into difference-weighted KNN classifiers, and finally develop two novel classifiers for pulse waveform classification. The experimental results show that the proposed classifiers are effective for accurate classification of pulse waveform.

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Spatial and Spectrum Feature Extraction signal and further present a Hilbert-Huang transform-based method for spectrum feature extraction. Finally, support vector machine is applied for computation pulse diagnosis. Experiment results show that the proposed method is effective and promising in distinguishing healthy people from patients with cholecystitis or nephritis.

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Edit Distance for Pulse DiagnosisP kernel, then embed them into difference-weighted KNN classifiers, and finally develop two novel classifiers for pulse waveform classification. The experimental results show that the proposed classifiers are effective for accurate classification of pulse waveform.

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Book 2018researchers, 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..