This book systematically introduces deep learning-based communication signal recognition and classification technologies. It first introduces fundamental neural networks and their applications in communication signal recognition, then systematically elaborates on deep learning-based classification and recognition methods for communication signals under small-sample conditions, and finally discusses deep learning-based specific emitter identification techniques. The book emphasizes the integration of theory and practice, proposing corresponding technical approaches for signal recognition scenarios that may arise in real-world environments. It includes both explanations of fundamental concepts and in-depth simulation analyses. This book can serve as a textbook or reference for undergraduate and postgraduate students in military and civilian programs such as Information and Communication Engineering, Cyberspace Security, and Electronic Countermeasure Engineering. It is also suitable for researchers and engineering technicians in the communication field to study and reference.

Xu Hua is currently a Professor in the Air Force Engineering University, Xi'an, China. His research focuses on communication signal processing, blind signal processing, communication countermeasures.  He has published 10+ papers in IEEE such as IEEE Transactions on Cognitive communication and Networkings and IEEE Transactions on Aerospace and Electronic Systems.

Shi Yunhao is currently a Lecturer in the Air Force Engineering University, Xi'an, China. His research interests include deep learning, signal processing and few-shot learning.

Jiang Lei is currently a Professor in the Air Force Engineering University, Xi'an, China. His research interests include communication system, electronic countermeasures and pattern recognition.

Qi Zisen is currently an Associate Professor with the Air Force Engineering University, Xi'an, China. His research interests include communication systems and array antenna.