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Net4AI 3af8eeba5d | 3 years ago | |
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.DS_Store | 3 years ago | |
CIFAR.zip | 3 years ago | |
Finger movement detection.zip | 3 years ago | |
MNIST.zip | 3 years ago | |
README.md | 3 years ago | |
~$adme (1).docx | 3 years ago |
Pleasue use Matlab 2018b or above to run the simulations.
The simulations consist of three main files: MINST,CIFAR, and Finger movement detection.
To run MINST, one must first download the MINST dataset. Then, one can run the code MIN-CPU.m or MIN-GPU.m.
CIFAR is used for image identification. Before running the code CIFAR.m, one must first run the code DownloadCIFAR10.m to downlowd the dataset of CIFAR. After that, one must run the code
% if ~exist('cifar10Train','dir')
% disp('Saving the Images in folders. This might take some time...');
% saveCIFAR10AsFolderOfImages('cifar-10-batches-mat', pwd, true);
% end
to classify the CIFAR dataset. Then, one can directly run the code CIFAR.m.
For finger movement detection, the data that has been processed by the window method can be downloaded from the links:
https://code.ihub.org.cn/attachments/download/952/Finger%20movement%20detection%20data%201.zip
https://code.ihub.org.cn/attachments/download/953/Finger%20movement%20detection%20data%202.zip
We need to download all data and put it into the “Finger movement detection” folder before running the code FMD.m.
In coding setting, stSettings.type determine the coding method. For example, stSettings.type=2 implies that Dithered 2-D lattice quantization method is used for coding while stSettings.type=3 implies that Dithered scalar quantization is used for coding. s_fRate determines the number of bits used to represent one element in the local FL model vector.
Net4AI 是未来(6G)内生智慧网络的两大技术发展方向之一,该方向的研究目标为充分利用网络节点的通信、计算和感知能力,通过分布式学习、群智式协同以及云边端一体化算法部署,支撑更为强大的网络智能(Network Intelligence),以实现未来各种智慧应用。本项目将对Net4AI相关论文的实现代码进行汇总,方便相关论文结果的复现,以促进该领域的健康发展。
Unity3D Asset CSV Text Python MATLAB other
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