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Automatic Modulation Classification Using Combination of Genetic Programming and KNN
This paper explores the use of Genetic Programming in combination with K-nearest neighbor (KNN) for AMC and demonstrates that the proposed method provides better classification performance compared to other recent methods.
Algorithms for automatic modulation recognition of communication signals
This paper introduces two algorithms for analog and digital modulations recognition that utilizes the decision-theoretic approach in which a set of decision criteria for identifying different types of modulations is developed and the artificial neural network is used as a new approach.
Automatic identification of digital modulation types
Noninvasive fetal electrocardiogram extraction: blind separation versus adaptive noise cancellation
A BSS procedure based on higher-order statistics and Widrow's multireference adaptive noise cancelling approach is compared and the experimental outcomes demonstrate the more robust performance of the blind technique and verify the validity of the BSS model in this important biomedical application.
Significantly Fast and Robust Fuzzy C-Means Clustering Algorithm Based on Morphological Reconstruction and Membership Filtering
An improved FCM algorithm based on morphological reconstruction and membership filtering (FRFCM) that is significantly faster and more robust than FCM is proposed in this paper and demonstrates that the proposed algorithm not only achieves better results, but also requires less time than the state-of-the-art algorithms for image segmentation.
Global gene expression analysis of human erythroid progenitors.
4 distinct populations at successive erythropoietin-dependent stages of erythroid maturation, including the terminal, pyknotic stage are isolated, demonstrating the importance of using defined cell populations to identify lineage and temporally specific patterns of gene expression.