An Intelligent Algorithm for Blood Cell Recognition Based on HHT-BPNN

Authors

  • Lixia Wan, Wei Long, Fugui Li & Liang Luo

DOI:

https://doi.org/10.3993/jfbim00113

Keywords:

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

Abstract

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

Published

2015-08-01

Issue

Section

Articles