Özen, AliOzturk, Celal2025-02-242025-02-242013978-1-4673-5563-6978-1-4673-5562-92165-06082-s2.0-84880876773https://hdl.handle.net/20.500.14440/76521st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26 -- 2013 -- CYPRUSA new digital modulation recognition method has been proposed for classifying baseband signals that are subjected to additive white Gaussian noise (AWGN) channel in this paper. The proposed method (ABC-ANN) is based on artificial neural network (ANN) which is trained by artificial bee colony (ABC) algorithm. The high order cumulants have been employed in the proposed ABC-ANN classifier. ABC algorithm has been used in finding the optimal weight set which directly affects the performance of artificial neural networks. Computer simulation results have demonstrated that the proposed recognizer can reach much better classification accuracy than the existing methods in even -5 dB of signal to noise ratio (SNR) value.trinfo:eu-repo/semantics/closedAccessModulation recognitionABC algorithmABC-ANNhigh order cumulantoptimizationConference ObjectN/AWOS:000325005300202N/A