(untitled) (Journal of Fiber Bioengineering and Informatics, 2015)
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.