惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园 - 叶小钗
WordPress大学
WordPress大学
Hugging Face - Blog
Hugging Face - Blog
T
Tailwind CSS Blog
博客园 - 三生石上(FineUI控件)
量子位
月光博客
月光博客
人人都是产品经理
人人都是产品经理
U
Unit 42
S
SegmentFault 最新的问题
M
MIT News - Artificial intelligence
H
Help Net Security
aimingoo的专栏
aimingoo的专栏
Microsoft Security Blog
Microsoft Security Blog
MyScale Blog
MyScale Blog
美团技术团队
P
Proofpoint News Feed
Apple Machine Learning Research
Apple Machine Learning Research
D
Docker
B
Blog
大猫的无限游戏
大猫的无限游戏
V
Visual Studio Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
G
Google Developers Blog

eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
BUPTCMCC-6G-DataAI+: A generative channel dataset for 6G ...
Li Yu, Jianhua Zhang, Mingjun Fu, Qixing Wang · 2024-09-30 · via eess.SP updates on arXiv.org

In September 2024, Beijing University of Posts and Telecommunications and China Mobile Communications Group jointly releases a channel dataset for the sixth generation (6G) mobile communications, named BUPTCMCC-6G-DataAI+. BUPTCMCC-6G-DataAI+ is the update version of BUPTCMCC-6G-DataAI, which is already published in June 2023, aiming at extending 6G new technologies, frequency bands, and applications. BUPTCMCC-6G-DataAI+ provides deterministic data covering new mid-bands, millimeter wave (mmWave), and terahertz (THz), supports the features of XL-MIMO near-field, high mobility and provides multiple 6G scenarios such as reconfigurable intelligent surface (RIS) and industrial Internet. Configured with customized features according to different user needs, BUPTCMCC-6G-DataAI+ can adaptively generate scalable large-scale or small-scale parameters, providing data support for 6G research and development, and standardization.