中文摘要：

针对已知的视觉诱发电位信号处理及特征提取存在的抗干扰能力差及识别率低的问题,提出一种基于B样条小波变换与BP神经网络的视觉诱发电位（VEP）的特征提取及识别方法。首先,对VEP进行少次平均预处理,以增强信号的信噪比;其次,基于B样条小波变换对VEP进行特征选取,并通过BP神经网络分类器对特征进行分类。与现有方法相比,所提出的方法能够较好地提取视觉诱发电位特征,对于含噪声的信号具有较好的抗干扰能力和识别能力。实验结果表明,采用B样条小波变换结合BP神经网络的方法,对视觉诱发电位的平均识别率为90.4%,优于其他方法,验证了所提出方法的正确性和有效性。

英文摘要：

With the aim to solve the problems such as weak anti-disturbances and low recognition rate in signal processing and feature extraction of visual evoked potential（ VEP）,a method based on the B-spline wavelet transform and BP neural network was proposed to extract and recognize the features of VEP.VEP was preprocessed by a few times of average to enhance the signal-noise ratio;Then based on the B-spline wavelet transform,features were extracted and classified with BP neural network classifier.Compared with existing methods,the experimental results showed that the proposed method could accurately extract the features of VEP,and display better performance on anti-disturbances and classification.The experiment results demonstrated that the method based on B-spline wavelet transform combined with BP neural network had an average recognition rate of 90.4%,displaying the feasibility and the effectiveness of the proposed method.