yassirajalil's repositories

5gm-data

Datasets and code for machine learning in 5G mmWave MIMO systems involving mobility (5GMdata)

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Automatic-Modulation-Classification

Some Code for Master Thesis - Research on Deep Learning Based Modulation Recognition Technologies

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Awesome-Cellular-Hacking

Awesome-Cellular-Hacking

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Bandswitch-DeepMIMO

Code for my publication: Deep Learning Predictive Band Switching in Wireless Networks. Paper under review.

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Begin-Latex-in-minutes

📜 Brief Intro to LaTeX for beginners that helps you use LaTeX with ease.

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cell-free-book

Simulation code for the monograph "Foundations of User-Centric Cell-Free Massive MIMO" by Özlem Tugfe Demir, Emil Björnson and Luca Sanguinetti, published in Foundations and Trends in Signal Processing, 2021.

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contiki-ng

Contiki-NG: The OS for Next Generation IoT Devices

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Deep-Reinforcement-Learning-Hands-On

Hands-on Deep Reinforcement Learning, published by Packt

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dlbook_exercises

Exercises for the Deep Learning textbook at www.deeplearningbook.org

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DRL-for-microgrid-energy-management

We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a population of thermostatically controlled loads, a population of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate between the different sources of flexibility by defining the priority resources, the direct demand control signals and the electricity prices. Seven deep reinforcement learning algorithms are implemented and empirically compared in this paper. The numerical results show a significant difference between the different deep reinforcement learning algorithms in their ability to converge to optimal policies. By adding an experience replay and a second semi-deterministic training phase to the well-known Asynchronous advantage actor critic algorithm, we achieved considerably better performance and converged to superior policies in terms of energy efficiency and economic value.

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DynaProg

Solve multi-stage deterministic decision problems with Dynamic Programming

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Energy-Efficiency-in-Reinforcement-Learning

Code for the paper 'Energy Efficiency in Reinforcement Learning for Wireless Sensor Networks'

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gym

A toolkit for developing and comparing reinforcement learning algorithms.

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heatmap

RF frequency heatmap using Google Maps API

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Internet-of-Things-Projects-with-ESP32

Hands-On Internet of things with ESP32, published by Packt

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introtodeeplearning

Lab Materials for MIT 6.S191: Introduction to Deep Learning

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line-solver

LINE - Performance and Reliability Analysis Engine

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machine-learning-for-telecommunications

A base solution that helps to generate insights from their data. The solution provides a framework for an end-to-end machine learning process including ad-hoc data exploration, data processing and feature engineering, and modeling training and evaluation. This baseline will provide the foundation for industry specific data to be applied and models created to release industry specific ML solutions.

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matlab-with-python

Files demonstrating MATLAB and Python interoperability

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Modulation-Classification-Deep-Learning-CNNs-

Deep Learning models to classify modulation techniques used in signals from DeepSig Dataset: RadioML 2016.04C

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neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

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Next-Generation-5G-OFDM-Based-Modulations

Compilation of the different MATLAB codes that were used for the experimental part of the research work presented in the article "Next Generation 5G OFDM-Based Modulations for Intensity Modulation-Direct Detection (IM-DD) Optical Fronthauling".

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paper-tips-and-tricks

Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.

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pwc

Papers with code. Sorted by stars. Updated weekly.

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RTLSDR-Scanner

A cross platform Python frequency scanning GUI for the OsmoSDR rtl-sdr library

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t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

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Thesis_Code_Automatic-Modulation-Classification

Implementation of various Machine Learning Classifiers for my thesis 'Machine Learning Techniques for Automatic Modulation Classification'

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Utilizing-SURF-Features-and-KLT-Tracking-Algorithm-in-Augmented-Reality-AR-Using-Kinect-V.-2-with

Utilizing SURF Features and KLT Tracking Algorithm in Augmented Reality (AR), Using Kinect V. 2 with the Aim of Autism Therapy

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