JCK-1096

JCK-1096's Stars

• jakevdp/PythonDataScienceHandbook

  Python Data Science Handbook: full text in Jupyter Notebooks

  Language:Jupyter Notebook43.6k1.8k19418k

• Pierian-Data/Complete-Python-3-Bootcamp

  Course Files for Complete Python 3 Bootcamp Course on Udemy

  Language:Jupyter Notebook27.7k2.7k35885.7k

• srsran/srsRAN_4G

  Open source SDR 4G software suite from Software Radio Systems (SRS) https://docs.srsran.com/projects/4g

  Language:C++3.6k2431.1k1.2k

• kfoofw/bandit_simulations

  Bandit algorithms simulations for online learning

  Language:Jupyter Notebook815133

• vli02/leetcode

  My leetcode solutions in C

  Language:C671027

• LABORA-INF-UFG/NetSoft2020-Tutorial4

  338214

• GZHU-DVL/tau-epsilon-greedy-RL

  The code for the article "(\tau,\epsilon)-GREEDY REINFORCEMENT LEARNING FOR ANTI-JAMMING WIRELESS COMMUNICATIONS"

  Language:Python26125

• IIT-Lab/Spectrum-Power-Allocation

  Deep Reinforcement Learning for Joint Spectrum and Power Allocation in Cellular Networks code

  Language:Python5105

• JCK-1096/Bandit-and-Reinforcement-Learning

  Python implementation for Reinforcement Learning algorithms -- Bandit algorithms, MDP, Dynamic Programming (value/policy iteration), Model-free Control (off-policy Monte Carlo, Q-learning)

  Language:Python1000

• JCK-1096/bayesla-link-adaptation

  Bayesian Link Adaptation under a BLER Target

  Language:Jupyter Notebook1000

• JCK-1096/CommPy

  Digital Communication with Python

  Language:Python1000

• JCK-1096/decentralized_qlearning_resource_allocation_in_wns

  Language:TeX10

• JCK-1096/Deep-Reinforcement-Learning-for-Dynamic-Spectrum-Access

  Using multi-agent Deep Q Learning with LSTM cells (DRQN) to train multiple users in cognitive radio to learn to share scarce resource (channels) equally without communication

  Language:Jupyter Notebook1000

• JCK-1096/DRL_for_DDBC

  Simulation codes for the manuscript "Deep Reinforcement Learning for Distributed Dynamic MISO Downlink-Beamforming Coordination" submitted to IEEE Transactions on Communications

  Language:Python1000

• JCK-1096/gr-ofdm

  Out-of-tree module for GNU Radio containing a complete OFDM implementation including GUI for reasearch and teaching

  Language:Python1100

• JCK-1096/IoT-MAB

  Decentralized Intelligent Resource Allocation for LoRaWAN Networks

  Language:Python1000

• JCK-1096/ITU-Challenge-ML5G-PHY-RL

  Scripts for the "ITU-ML5G-PS-006: ML5G-PHY-Reinforcement learning: scheduling and resource allocation"

  Language:Python1000

• JCK-1096/mabwiser

  [IJAIT 2021] MABWiser: Contextual Multi-Armed Bandits Library

  Language:Python1000

• JCK-1096/MARLforChannelBondingWLANs

  WLAN channel access through Multi-Agent Reinforcement Learning (MARL)

  Language:Jupyter Notebook100

• JCK-1096/MP-MAB

  This project is created for the simulations of the paper: [Wang2021] Wenbo Wang, Amir Leshem, Dusit Niyato and Zhu Han, "Decentralized Learning for Channel Allocation inIoT Networks over Unlicensed Bandwidth as aContextual Multi-player Multi-armed Bandit Game", to appear in IEEE Transactions on Wireless Communications, 2021.

  Language:Python100

• JCK-1096/NetSoft2020-Tutorial4

  1

• JCK-1096/PythonExamples

  Python coding examples for wireless communication systems. This includes currently the topics of modulation such as 4-QAM, BPSK (2-PSK) with an AWGN channel and also Rayleigh fading.

  100

• JCK-1096/Resource-allocation-in-Cognitive-Radio-

  Resource allocation for underlay DSA Cognitive Radio networks using reinforcement learning (Q-Learning))

  1

• JCK-1096/ResourceAllocationReinforcementLearning

  intial version

  1