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a-novel-ofdm-autoencoder-featuring-cnn-based-channel-estimation-for-internet-of-vessels

paper code of A-Novel-OFDM-Autoencoder-Featuring-CNN-Based-Channel-Estimation-for-Internet-of-Vessels

autoencoder_communication_system_wgan_channel-estimation

Master Thesis compairing Communicationsystems Baised on GAN and baised on MI

autoencoders_tensorflow

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

cad_cfo_estimation

channelnet

Implementation of the paper "Deep Learning-Based Channel Estimation"

colab-hacks

Simple Hacks for Google Colaboratory to boost your productivity and help you to perform daily tasks.

complete-python-3-bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

complete-python-bootcamp

Lectures for Udemy - Complete Python Bootcamp Course

d-amp_toolbox

This package contains the code to run Learned D-AMP, D-AMP, D-VAMP, D-prGAMP, and DnCNN algorithms. It also includes code to train Learned D-AMP, DnCNN, and Deep Image Prior U-net using the SURE loss.

dataset

Open RadioML Synthetic Benchmark Dataset

deep-learning-based-csi-estimation-for-5g-communication

A framework to estimate the Channel State Information for a 5G communication

deep-learning-channel-estimation

Simulation code for “Channel Estimation in Massive MIMO under Hardware Non-Linearities: Bayesian Methods versus Deep Learning,” by Özlem Tugfe Demir, Emil Björnson, IEEE Open Journal of the Communications Society, To appear.

deep-mimo-detection

Data for IEEE Trans. Broadcasting Paper: M. Baek, S. Kwak, J. Jung, H. M. Kim and D. Choi, "Implementation Methodologies of Deep Learning-Based Signal Detection for Conventional MIMO Transmitters," in IEEE Transactions on Broadcasting, vol. 65, no. 3, pp. 636-642, Sept. 2019.

deep-symbolic-optimization

Source code for deep symbolic optimization.

deepfreq

Code, Pre-trained Models and some materials accompanying "Data-driven Estimation of Sinusoid Frequencies"

deepinsight

A methodology to transform a non-image data to an image for convolution neural network architecture

dnn_detection_via_keras

This is the simplest implementation of Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems using keras.

dockerrml

Docker images set up with tools for radio & machine learning tasks

docs

TensorFlow documentation

estimation-theory

Code for working on Estimation Theory based problems from Dr. Todd Humphrey's ASE381K course at UT Austin

eveai

A Deep Learning Library based on python Keras and Tensorflow. Support for x86/x64 windows application.

examples

Useful RadioML Examples

feature-selection-using-genetic-algorithm

Feature selection is performed using genetic algorithm to make a robust predictive model on the Boston dataset.

gan_tensorflow

Automatic feature engineering using Generative Adversarial Networks using TensorFlow.

geneticfs

GeneticFS is a library for feature selection in Machine Learning using a Genetic Algorithm as an optimisation method.

gentun

Hyperparameter tuning for machine learning models using a distributed genetic algorithm

handong1587.github.io

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

hyperparameters-tuning-genetic-algorithm

Exploring how to evolve a neural network and its hyperparameters through a genetic algorithm

joint_cfo_channel_camsap_2017

This directory contains all the codes required to reproduce the results in our CAMSAP 2017 paper titled "Joint CFO and channel estimation in millimeter wave systems with one-bit ADCs"