… is the introduction of two deep learning networks for MIMO … against the MBest sphere
decoding algorithm as presented in [… M-Best SD M = 5: The M-Best sphere decoding algorithm, …

… We apply the Viterbi decoder to get the raw data by minimizing the hamming distance. Fig.
5 … Usually, we implement the deep learning framework TensorFlow [29] to train the CNN …

… of Machine Learning, and Geometric Deep Learning in particular. Most closely related to
ours are approaches based on designing steerable filters, which can learn representations that …

… In this paper, we used a deep learning approach with ܭ and ܭͳ sphere decoders to significantly
improve performance in terms of BER, spectral efficiency, and computational complexity …

… -driven deep learning models for decoding executed … /D oscillations in deep learning to
decode the unimanual and … our proposed deep learning model for decoding executed unimanual …

… decoding is imperfect in the real-world NOMA system, we propose a novel scheme for the
downlink of the MIMO-NOMA system based on deep learning. … -complexity sphere decoding for …

… of decoders includes sphere decoding methods based on lattice points enumeration and
radius adaptation. The complexity of sphere decoding … Detection based on sphere decoding is …

… Deep learning models have achieved great success in supervised shape descriptor learning
… However, the unsupervised shape descriptor calculated via deep learning is less studied …

… approach for decoding visually imagined … deep learning (DL) framework to automatically
extract features from the constructed joint TFS representation of the EEG signals and decode …

… In a concurrent work, a deep learning lattice decoder is also proposed in [12]. In this paper,
we aim to present a neural network decoding algorithm for lattices constructed based on …