… In the second system model, two deep learning-assisted algorithms … We propose a deep
learning modified orthogonal … on deep learning-based data detection and channel decoding of …

… a DNN-based decoder is almost the same as that of a MPA decoder, even though the
computational complexity of a DNNbased decoder is much less than that of a MPA decoder. In Fig. …

… scheme based on slicing sphere decoder (SD) to mitigate intrinsic ISI and ICI at a cost of
acceptable computational complexity. As the data length decoded each time increases, the …

… In this study, the authors apply sphere decoder (SD) with box optimisation (BO) to reduce
inter-carrier interference (ICI) in the FTN non-orthogonal frequency division multiplexing (FTN–…

… as pronounced dissipation when learning operators in spherical coordinates by incorrectly …
FNOs on the sphere, introducing Spherical FNOs (SFNOs) for learning operators on spherical …

… Figure 1 illustrates our deep learning scheme for transmitting polarization images through
… deep learning approach introduced in this work unlocks the concept of machine learning …

… Specifically, we extend our framework to perform deep learning tasks on NeRFs by directly
processing their MLPs weights. • The processing of MLPs parametrizing NFs has been …

… To this effect, we apply deep learning to enhance the luminescence imaging resolution of
lanthanide-doped NCs, achieving successful information storage and readout through pork …

… MIMO systems employing sphere decoding (SD) algorithm … the candidate search space to
a sphere of a certain radius. The … The significance of deep learning in signal processing and …

… Section IV elaborates on major findings by addressing six major questions: (1) How deep
learning is changing machine learning in EEG-based imagined speech decoding? (2) What is …