Automatic Modulation Classification Using Cyclic Correntropy Spectrum in Impulsive Noise
Automatic Modulation Classification Using Cyclic Correntropy Spectrum in Impulsive Noise is a scholarly work, published in 2019 in ''IEEE Wireless Communications Letters''. The main subjects of the publication include modulation, independent component analysis, classifier, artificial intelligence, noise, computer science, artificial neural network, speech recognition, principal component analysis, pattern recognition, algorithm, and radial basis function. Monte Carlo simulations demonstrate that the proposed algorithm outperforms other existing schemes in impulsive noise cases, especially with a low generalized signal to noise ratio.