基于CNN的调制识别.py下载

基于CNN的调制识别，keras框架，tensorflow后端，数据集为github通用数据集。 We survey the latest advances in machine learning with deep neural networks by applying them to the task of radio modulation recognition. Results show that radio modulation recognition is not limited by network depth and further work should focus on improving learned synchronization and equalization. Advances in these areas will likely come from novel architectures designed for these tasks or through novel training methods.