The demand for bandwidth-critical applications has stimulated the research community not
only to develop new ways of communication, but also to use the existing spectrum efficiently …

Genetic Programming (GP) has been successfully applied to image classification and
achieved promising results. However, most existing methods either address binary image …

High-fidelity multi-scale design optimization of many real-life applications in structural
engineering still remains largely intractable due to the computationally intensive nature of …

This paper presents a novel hybrid extreme learning machine (ELM) with cuckoo search
algorithm (CSA) for the classification purposes of the digitally modulated signals, such as …

With the commercialization of 5G, in order to recognize QAM signals, one of the main
modulation modes in 5G communication systems, this paper put forward the BP-BSA …

Recently, deep learning models have been widely applied to modulation recognition, and
they have become a hot topic due to their excellent end-to-end learning capabilities …

Neural network shows great potential in modulation classification because of its excellent
accuracy and achievability but overfitting and memorizing data noise often happen in …

Automatic modulation classification (AMC) has been identified to perform a key role to
realize technologies such as cognitive radio, dynamic spectrum management, and …

With the advancement of internet technologies and multimedia applications, the spectrum
scarcity problem is becoming more acute. Thus, spectral-efficient schemes with minimal …

Due to the neglect of the retrieval of communication parameters (including the symbol rate,
the symbol timing offset, and the carrier frequency), the existing non-cooperative …