Automatic digital modulation recognition using artificial neural network and genetic algorithm
Signal Processing - Special issue on independent components analysis and beyond
Online modulation recognition of analog communication signals using neural network
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
Expert Systems with Applications: An International Journal
Semi-blind algorithms for automatic classification of digital modulation schemes
Digital Signal Processing
Expert Systems with Applications: An International Journal
Radio frequency fingerprinting commercial communication devices to enhance electronic security
International Journal of Electronic Security and Digital Forensics
Digital Modulation identification model using wavelet transform and statistical parameters
Journal of Computer Systems, Networks, and Communications
Multiclass least-squares support vector machines for analog modulation classification
Expert Systems with Applications: An International Journal
Underdetermined BSS of MISO OSTBC Signals
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Wireless Personal Communications: An International Journal
Digital Signal Processing
Comparison of clustering algorithms for analog modulation classification
Expert Systems with Applications: An International Journal
A wavelet-based method for classification of binary digitally modulated signals
SARNOFF'09 Proceedings of the 32nd international conference on Sarnoff symposium
EURASIP Journal on Advances in Signal Processing - Special issue on dynamic spectrum access for wireless networking
Improved wireless security for GMSK-based devices using RF fingerprinting
International Journal of Electronic Security and Digital Forensics
Signal classification in fading channels using cyclic spectral analysis
EURASIP Journal on Wireless Communications and Networking
Universal classifier and synchroniser
International Journal of Autonomous and Adaptive Communications Systems
Multi-user signal classification via spectral correlation
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
Sarnoff'10 Proceedings of the 33rd IEEE conference on Sarnoff
Methods of digital modulation recognition and their testing
ICCOM'10 Proceedings of the 14th WSEAS international conference on Communications
Algorithms of digital modulation classification and their verification
WSEAS TRANSACTIONS on COMMUNICATIONS
Expert Systems with Applications: An International Journal
Cyclostationarity-based blind classification of analog and digital modulations
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
M-ary frequency shift keying signal classification based-on discrete Fourier transform
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume II
Recognition of digital modulations based on mathematical classifier
ECS'10/ECCTD'10/ECCOM'10/ECCS'10 Proceedings of the European conference of systems, and European conference of circuits technology and devices, and European conference of communications, and European conference on Computer science
Modulation classification for burst-mode qam signals in multipath fading channels
Iranian Journal of Science and Technology, Transaction B: Engineering
Modulation classifier of digitally modulated signals based on method of artificial neural networks
AEE'05 Proceedings of the 4th WSEAS international conference on Applications of electrical engineering
Digital Signal Processing
Selection of optimal features for digital modulation recognition
ICOSSSE'11 Proceedings of the 10th WSEAS international conference on System science and simulation in engineering
Identification of radio disturbances of wireless sensor networks
Proceedings of the 2013 Summer Computer Simulation Conference
| Hi-index | 0.01 |
From the Publisher:Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the correct modulation type of a signal: to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communication Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a critical review of automatic modulation recognition. This includes techniques for recognising digitally modulated signals. The book also gives comprehensive treatment of using artificial neural networks for recognising modulation types.