TY - JOUR
T1 - An Intelligent Algorithm for Blood Cell Recognition Based on HHT-BPNN
AU - Lixia Wan, Wei Long, Fugui Li & Liang Luo
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.