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Edit Distance for Pulse Diagnosis

  • David Zhang
  • Wangmeng Zuo
  • Peng Wang
Chapter

Abstract

In this chapter, by referring to the edit distance with real penalty (ERP) and the recent progress in k-nearest neighbors (KNN) classifiers, we propose two novel ERP-based KNN classifiers. Taking advantage of the metric property of ERP, we first develop an ERP-induced inner product and a Gaussian ERP 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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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • David Zhang
    • 1
  • Wangmeng Zuo
    • 2
  • Peng Wang
    • 3
  1. 1.School of Science and EngineeringThe Chinese University of Hong KongShenzhenChina
  2. 2.Harbin Institute of TechnologyHarbinChina
  3. 3.Northeast Agricultural UniversityHarbinChina

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