Study of human identity recognition based on HMM and WNN
基于HMM和WNN的心音信号身份识别研究*

Used HMM combined with WNN, this paper proposed a human identity recognition method based on heart sound signal. First, employed HMM to train the time sequence of heart sounds and to compute the Viteribi output score. Then used the score as the input of WNN, made nonlinear mapping by WNN to acquire the classification information. The result of recognition was made by these two kinds of recognition information. The experiment collected 160 heart sounds from 80 people to test the proposed algorithm, the proposed system achieved higher recognition rate than Gaussian mixture model method. The results show that the hybrid model can effectively improve the recognition performance of the system and achieve a satisfactory effect.