A deep learning-based communication interference intelligent identification method

Abstract

The application provides a kind of communication interference intelligent identification method based on deep learning, belongs to communication data processing technical field, to adopt space-time two-way memory resonance network and antagonistic complementary training framework, can deeply mine the space-time coupling characteristics in communication data and accurately identify various kinds of interference in small sample environment.The application realizes dynamic coupling and mutual modulation of time and space characteristics in the extraction stage by constructing a space-time two-way memory resonance network, breaking through the limitations of feature separation processing in traditional methods, so that the model can deeply mine and understand the propagation and evolution law of interference in time and space dimensions, and improve the discovery and identification ability of early micro signs and complex coupled interference.