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A Modular Neural Network Based Deep Learning Approach for MIMO Signal Detection
Motivated by this finding, we propose a novel modular neural network based approach, termed MNNet, where the whole network is formed by a set of pre-defined ANN modules.
On Deep Learning Solutions for Joint Transmitter and Noncoherent Receiver Design in MU-MIMO Systems
Otherwise, it is called non-systematic waveform, where no artificial design is involved.
A Benchmark for Voice-Face Cross-Modal Matching and Retrieval
In this paper, a baseline evaluation framework is proposed for voice-face matching and retrieval tasks.
End-to-End Learning for Uplink MU-SIMO Joint Transmitter and Non-Coherent Receiver Design in Fading Channels
In this paper, a novel end-to-end learning approach, namely JTRD-Net, is proposed for uplink multiuser single-input multiple-output (MU-SIMO) joint transmitter and non-coherent receiver design (JTRD) in fading channels.
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