fafa-ccnu

fafa-ccnu

Geek Repo

Company:CCNU

Location:Wuhan, China

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fafa-ccnu's repositories

RadioML_2018.01A_Architectures_Benchmark

📊 Benchmarking Machine Learning Architectures for RadioML (Radio Machine Learning) 📡

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Hands-on-RL

https://hrl.boyuai.com/

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DeepRL

Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone

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PytorchNetHub

项目注释+论文复现+算法竞赛+Pytorch指北

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astyx

An API to access the Astyx Hires dataset

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Deep-Reinforcement-Learning-Hands-On-Second-Edition

Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt

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DRL

Deep Reinforcement Learning

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easy-rl

强化学习中文教程,在线阅读地址:https://datawhalechina.github.io/easy-rl/

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mec_drl

Deep reinforcement learning for mobile edge computing

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introRL

Intro to Reinforcement Learning (强化学习纲要)

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gr-tutorial

A tutorial OOT module for GNU Radio

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SFND_Radar_Target_Detection

Project for Udacity's Sensor Fusion Engineer Nanodegree Program - Radar Target detection

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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

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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

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wireless-ml

Research on machine learning in wireless communications.

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996.ICU

Repo for counting stars and contributing. Press F to pay respect to glorious developers.

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py-radio-autoencoder

Python implementation of autoencoder based radio system

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Channel-Equalization-in-FBMC

Allows to reproduce all figures from "FBMC-OQAM in Doubly-Selective Channels: A New Perspective on MMSE Equalization", IEEE SPAWC, 2017.

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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/

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Deep-Learning-for-the-Physical-Layer

PyTorch implementation for part of paper "An Introduction to Deep Learning for the Physical Layer" by Kenta Iwasaki on behalf of Gram.AI.

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radio-transformer-networks

A PyTorch implementation of Radio Transformer Networks from the paper "An Introduction to Deep Learning for the Physical Layer".

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DL-ChannelDecoding

On Deep Learning-based Channel Decoding

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