Feedback process neural networks model with application in classification of dynamic signal
一种反馈过程神经元网络模型及在动态信号分类中的应用

To solve the classification of dynamic signal, this paper proposed a feedback process neural networks model and classification methods based on this model. The time-varying function could be directly used as input of this network. In addition to the existence of the feed-forward information flow like a normal neural network, there still existed the feedback information flow from output to input in this model, and the nodes could also form a self-feedback. The network could be directly used into pattern classification of dynamic signals. Improved the efficiency and stability of the network evidently with application of the feedback information from the neurons in output layer in the learning process of the feedback process neural networks. Ta-king the classification of time-varying functions as an example, the experimental results show that the model and the algorithm are efficient.