… a capsule network (CapsNet) for blind modulation classification. This paper addressed the
main issue of overlapped co-channel signals. However, the conventional capsule network …

… excellent generalization ability provided by capsule network. … PROPOSED METHOD Solving
AMC with capsule networks … capsule network directly after IF sampling, and classification …

… capsule network (CapsNet), we propose a new network structure named AMR-CapsNet to
achieve higher classification accuracy of modulation … likelihood modulation classification in flat …

… modulation classification in digitally modulated signals [7], [14]. In this paper we consider the
capsule network … 1, and we study its use in the context of classification of digitally modulated …

This paper presents a novel deep-learning (DL)-based approach for classifying digitally
modulated signals, which involves the use of capsule networks (CAPs) together with the cyclic …

… a capsule network (CapsNet) for blind modulation classification. This paper addressed the
main issue of overlapped co‑channel signals. However, the conventional capsule network …

… capsule network feature extraction block specifically designed for modulation signal
classification… and complex-valued networks to extract features from modulation signals, ultimately …

… of classifications, this paper utilizes the capsule (vector) length to represent the corresponding
category classification … Shu, ‘‘Automatic modulation classification of digital modulation …

… future directions in the area of DL for modulation classification. … Exploiting capsule networks
to address overlapped co-channel … Capsule layers to enrich representational features …

… Cov-Net is one of the earlier deep learning based automatic modulation classification
approaches, which contains two convolutional layers and two fully connected layers. It. By …