关键词: 希尔伯特黄变换（HHT）, 经验模态分解（EMD）, 神经网络, 血细胞识别, 特征提取

Abstract: Polymorphous blood cell signal affects cell classification and counting. This paper proposes an algorithm composed with Hilbert-Huang Transform（HHT）and neural network to recognize blood cell. The energy features of blood cell signal, extracted with empirical mode decomposition and Hilbert transform are combined with time domain features to constitute eigenvector. A model on neural network is built and trained and simulated to recognize blood cells. Simulation results show that the algorithm has high accuracy and good effect on recognition.

Key words: Hilbert-Huang Transform（HHT）, Empirical Mode Decomposition（EMD）, neural network, blood cell recognition, feature extraction