yujie2016

yujie2016's Stars

• JUNGJAEHOON-98/An-Introduction-to-Deep-Learning-for-the-Physical-Layer

  Language:Python5

• AndreaMSBios/Autoencoder-for-Physical-Layer

  Partly implemented paper "An Introduction to Deep Learning for the Physical Layer"

  Language:Jupyter Notebook6

• immortal3/AutoEncoder-Based-Communication-System

  Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/

  Language:Jupyter Notebook12477

• jcbooth2/autoencoder_for_physical_layer

  This is my attempt to reproduce and extend the results in the paper "An Introduction to Deep Learning for the Physical Layer" by Tim O'Shea and Jakob Hoydis

  Language:Jupyter Notebook5325

• qiurunze123/miaosha

  ⭐⭐⭐⭐秒杀系统设计与实现.互联网工程师进阶与分析🙋🐓

  Language:Java26.2k6.6k

• ML4Comm-Netw/Paper-with-Code-of-Wireless-communication-Based-on-DL

  无线与深度学习结合的论文代码整理/Paper-with-Code-of-Wireless-communication-Based-on-DL

  1.8k639

• gbaier/rake_ber_sim_python

  BER simulation of a Rake receiver using 16-QAM and a multipath channel with Rayleigh fading

  Language:Python101

• AjeyPaiK/JointTypicality

  This repository contains code to check if a good decoding scheme can be performed using AEP in a Binary Symmetric Channel and to verify the coding theorem.

  Language:Python1

• pierrebaudot/infotopopy

  computes most of information functions (joint entropy, conditional, mutual information, total correlation information distance) and deep information networks

  Language:Python338

• kirlf/ModulationPy

  Linear digital modems

  Language:Python3814

• tinyxuyan/AE-Com-Roadmap

  Collections of Papers and Codes about Communication Systems Built by Autoencoder

  5015

• Fritschek/Wireless_encoding_with_MI_estimation

  Implementation of an approach for wireless encoding via MI estimation

  Language:Jupyter Notebook1614

• Mryangkaitong/python-Machine-learning

  机器学习算法项目

  Language:Jupyter Notebook842328

• snowkylin/tensorflow-handbook

  简单粗暴 TensorFlow 2 | A Concise Handbook of TensorFlow 2 | 一本简明的 TensorFlow 2 入门指导教程

  Language:Jupyter Notebook3.9k841

• hlz1992/RadioCNN

  Language:Python2515

• sambklein/DistributionMatching

  Language:Jupyter Notebook1

• dario-pilori/dsp-library

  MATLAB library of DSP functions for optical communications

  Language:MATLAB3623

• FernandoGuiomar/OptDSP_lite

  Language:MATLAB3417

• mihaivarsandan/Probabilistic_Constellation_Shaping

  Language:MATLAB3417

• Rassibassi/claude

  End-to-end learning of optical communication systems

  Language:Python11244

• ssiillaass/QAMoRama

  neuronal demodulator 64QAM

  Language:MATLAB1

• mkudinov/DcnnDemodulation

  Reproducing "Demodulation of Faded Wireless Signals using Deep Convolutional Neural Networks"

  Language:Python12

• sethuramanio/GAN-for-wireless-communication

  In this repo, I develop an end-to-end wireless communication system using deep neural networks (DNNs), where DNNs are employed to perform several key functions, including encoding, decoding, modulation, and demodulation.

  Language:Jupyter Notebook31