Abstract：On automatic modulation there are two approaches, decision-theoretic and statistical pattem. An automatic modulation recognition system to recognize four digital signal classes as MASK, MFSK, MPSK, MQAM is proposed in this paper, which using decision-theoretic based feature set addition to statistical pattem based feature set with momentum auto-adapted weight BP neural network. Performance is generally good when Signal to Noise Ratios (SNR) in 0-10dB, and the estimated carrier frequency differs from the actual carrier frequency of 0-100Hz, simulations show the results even larger than 97%, that confirm the robustness and practicability of this recognition method.
赖惠成; 褚辉. 一种混合模式的神经网络自动调制识别器[J]. 电子与信息学报, 2008, 30(5): 1203-1205 .
Lai Hui-cheng; Chu Hui . An Automatic Modulation Recognizer Using Neural Networks Based on the Hybrid Mode. , 2008, 30(5): 1203-1205 .
2008, Vol. 30 
