Volume 8, Issue 2
An Intelligent Algorithm for Blood Cell Recognition Based on HHT-BPNN

Lixia Wan, Wei Long, Fugui Li & Liang Luo

Journal of Fiber Bioengineering & Informatics, 8 (2015), pp. 357-364.

Published online: 2015-08

Preview Purchase PDF 0 1767
Export citation
  • Abstract

For the blood cell signal has the characteristics of nonlinear, non-stationary and M-morphous, an intelligent algorithm for blood cell recognition based on Hilbert-Huang Transformation and BP Neural Network (HHT-BPNN) is put forward, which convert the time domain features of the blood cell signal into energy features by combining empirical mode decomposition with Hilbert transform, and put the time domain features and the energy features together as the feature vector. Then, a model based on BP neural network is built by training and simulating that complete the work of effective identification and accurate count for M-morphous blood cells. Simulation results show that the algorithm proposed has high recognition accuracy with good recognition performance.

  • Keywords

Blood Cell Recognition Hilbert-Huang Transform (HHT) BP Neural Network Empirical Mode Decomposition Feature Vector

  • AMS Subject Headings

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{JFBI-8-357, author = {}, title = {An Intelligent Algorithm for Blood Cell Recognition Based on HHT-BPNN}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2015}, volume = {8}, number = {2}, pages = {357--364}, abstract = {For the blood cell signal has the characteristics of nonlinear, non-stationary and M-morphous, an intelligent algorithm for blood cell recognition based on Hilbert-Huang Transformation and BP Neural Network (HHT-BPNN) is put forward, which convert the time domain features of the blood cell signal into energy features by combining empirical mode decomposition with Hilbert transform, and put the time domain features and the energy features together as the feature vector. Then, a model based on BP neural network is built by training and simulating that complete the work of effective identification and accurate count for M-morphous blood cells. Simulation results show that the algorithm proposed has high recognition accuracy with good recognition performance.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbim00113}, url = {http://global-sci.org/intro/article_detail/jfbi/4716.html} }
TY - JOUR T1 - An Intelligent Algorithm for Blood Cell Recognition Based on HHT-BPNN JO - Journal of Fiber Bioengineering and Informatics VL - 2 SP - 357 EP - 364 PY - 2015 DA - 2015/08 SN - 8 DO - http://doi.org/10.3993/jfbim00113 UR - https://global-sci.org/intro/article_detail/jfbi/4716.html KW - Blood Cell Recognition KW - Hilbert-Huang Transform (HHT) KW - BP Neural Network KW - Empirical Mode Decomposition KW - Feature Vector AB - For the blood cell signal has the characteristics of nonlinear, non-stationary and M-morphous, an intelligent algorithm for blood cell recognition based on Hilbert-Huang Transformation and BP Neural Network (HHT-BPNN) is put forward, which convert the time domain features of the blood cell signal into energy features by combining empirical mode decomposition with Hilbert transform, and put the time domain features and the energy features together as the feature vector. Then, a model based on BP neural network is built by training and simulating that complete the work of effective identification and accurate count for M-morphous blood cells. Simulation results show that the algorithm proposed has high recognition accuracy with good recognition performance.
Lixia Wan, Wei Long, Fugui Li & Liang Luo. (2019). An Intelligent Algorithm for Blood Cell Recognition Based on HHT-BPNN. Journal of Fiber Bioengineering and Informatics. 8 (2). 357-364. doi:10.3993/jfbim00113
Copy to clipboard
The citation has been copied to your clipboard