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Automatic modulation type identification is needed in many applications. Most of modulation type identification methods can only recognize a few kinds of signals. They usually require high levels of signal to noise ratio (SNR) to achieve an acceptable performance. This paper proposes a new intelligent digital modulation type identifier. This identifier uses a multilayer perceptron neural network with resilient back propagation learning algorithm as the classifier and higher order moments anddoi:10.1016/j.engappai.2007.06.003 fatcat:my7n56ysh5crji4fdst4cuhsgy