Convolutional and recurrent neural networks for real-time data classification

In this paper, methods of classification of real-time data are provided by using convolutional and recurrent neural networks. During the last several years, artificial intelligence researchers and specialists achieved notable results in visual, voice and natural language processing tasks by using new methods and approaches of deep learning, such as convolutional and recurrent neural networks. However, not much research is going on of usage such networks for elaboration of real-time data. The goal of this work is exploring, experimenting and providing new approaches of classification nonstationary data using above mentioned neural networks.