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Titlebook: Artificial Intelligence for Communications and Networks; First EAI Internatio Shuai Han,Liang Ye,Weixiao Meng Conference proceedings 2019 I

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樓主: legerdemain
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發(fā)表于 2025-3-30 12:16:39 | 只看該作者
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發(fā)表于 2025-3-30 15:12:46 | 只看該作者
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發(fā)表于 2025-3-30 18:49:41 | 只看該作者
Neural Networks in Hybrid Precoding for Millimeter Wave Massive MIMO Systemsve multiple-input multiple-output (MIMO) systems, hybrid precoding has been considered as an energy-efficient technology to replace fully-digital precoding. The way of designing hybrid precoding in mmWave massive MIMO systems by multi-layer neural networks has not been investigated. Based on further
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發(fā)表于 2025-3-30 20:42:47 | 只看該作者
A Reinforcement Learning Based Joint Spectrum Allocation and Power Control Algorithm for D2D Communi distributed multi-agent reinforcement learning (MARL) based joint SA-PC algorithm is proposed for performing spectrum allocation and power control for each D2D user in the network. The proposed algorithm uses Q learning, a typical form of reinforcement learning (RL), to select the optimal resource
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發(fā)表于 2025-3-31 01:46:16 | 只看該作者
Improved Neural Machine Translation with POS-Tagging Through Joint Decoding accuracy and latency than deep syntax such as dependency parsing. We present three NMT decoding models (independent decoder, gates shared decoder and fully shared decoder) to jointly predict target word and POS tag sequences. Experiments on Chinese-English and German-English translation tasks show
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發(fā)表于 2025-3-31 05:33:42 | 只看該作者
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發(fā)表于 2025-3-31 09:27:11 | 只看該作者
A Transfer Learning Method for Aircrafts Recognitionaging in different resolutions, different satellites and different imaging conditions, they obey different distributions. The Feature Subspace Alignment and Balanced Distribution Adaptation (FSA-BDA) method is proposed to solve this problem. Different from other transfer learning methods, it conside
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發(fā)表于 2025-3-31 14:55:42 | 只看該作者
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