Theories and Methods
Buch, Englisch, 353 Seiten, Format (B × H): 155 mm x 235 mm
ISBN: 978-981-9280-39-1
Verlag: Springer
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction.- Convolutional Neural Network Based Communication Signal Recognition.- Recurrent Neural Network and Hybrid Network-Based Communication Signal Recognition.- GAN Based Communication Signal Recognition.




