Judithcodes
I am a self taught Front-end developer and Machine learning engineer, veraciously seeking to learn more
Nigeria
Pinned Repositories
amc-toolbox
MATLAB toolbox for automatic modulation classifier development
AugmentedAutoencoder
Official Code: Implicit 3D Orientation Learning for 6D Object Detection from RGB Images
Autoencoder_communication_system_WGAN_Channel-estimation
Master Thesis compairing Communicationsystems Baised on GAN and baised on MI
Autoencoder_communication_sytem_with_GAN_channel-estimation
Communication System with GAN based Channel estimation
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
DeepHybridBeamforming
% These MATLAB scripts are prepared by A.M.E for the following paper, % A. M. Elbir, "CNN-Based Precoder and Combiner Design in mmWave MIMO Systems," IEEE Communications Letters, vol. 23, no. 7, pp. 1240-1243, July 2019 % please cite the above work if you use this codes, % For any comments and questions please email: ahmetmelbir@gmail.com %
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
Text-Emotion-Recognition
A repository for recognizing emotion in tweets
UAV-in-Cognitive-Radio-Network
Judithcodes's Repositories
Judithcodes/amc-toolbox
MATLAB toolbox for automatic modulation classifier development
Judithcodes/Channel-Estimation-OFDM-
-Investigated the efficiency of different estimators to estimate and track channel parameters based on the Mean Squared Error (MSE) performance. The estimators employed in the simulation are LS and MMSE estimators and their performance in the transfer domain was evaluated. MATLAB was used for the simulation of the communication link and analyzing the error between the estimated channel parameters and actual modeled channel parameters.
Judithcodes/In-Band-Scheduling-and-User-Association-in-5G-HetNets
Matlab Simulation for T. K. Vu, M. Bennis, S. Samarakoon, M. Debbah and M. Latva-aho, "Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks," European Wireless 2016; 22th European Wireless Conference, Oulu, Finland, 2016, pp. 1-6. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7499273&isnumber=7499250
Judithcodes/Label-Consistent-Autoencoder
This is a MATLAB function implementing an autoencoder which incorporates label information.
Judithcodes/MIMO
An exploratory project on matlab stimulation of a wireless MIMO system using bpsk zero forcing technique
Judithcodes/MIMOChannelEstimator
MIMO OFDM channel estimation using time delay neural network in matlab simulink
Judithcodes/MISTWF-toolkit-simulation
Matlab implementation and simulation infrastructure of the algorithm in "An Alternative Perspective on Utility Maximization in Energy-Harvesting Wireless Sensor Networks" by Roseveare and Natarajan
Judithcodes/modulationclassification_matlab
MATLAB files of modulation classification in cognitive radios
Judithcodes/Nonnegativity-Constrained-Autoencoder-NCAE
Matlab code for implementing Nonnegativity Constrained Autoencoder (NCAE) for Deep Learning.
Judithcodes/OptimalSensorPlacement
Matlab code to reproduce the figure of the paper "Near-optimal sensor placement for linear inverse problems"
Judithcodes/SensorPlacement
Matlab Code used in the paper: Sensor placement by maximal projection on minimum eigenspace for linear inverse problems, IEEE-TSP, 2016
Judithcodes/AdaptiveModulationML
Adaptive Modulation using k-NN classification for OFDM system
Judithcodes/AnomalyDetectionToolbox
A collection of algorithms for anomaly detection
Judithcodes/Antennas-placement
Parallels solutions for antenna's placement problem.
Judithcodes/AutoEncoder
Implementation of Semantic Hashing. Modified from Ruslan Salakhutdinov and Geoff Hinton's code of training Deep AutoEncoder
Judithcodes/autoencoder-1
Reducing the Dimensionality of Data with Neural Network
Judithcodes/autoencoders_arcene
Modeling High-Dimensional Classification Problems Using Deep Learning
Judithcodes/cnn
Convolutional ANN using RadioML data
Judithcodes/crSimulator
Model for Cognitive Radio Ad hoc Network Simulations in OMNeT++
Judithcodes/Deep-Learning-Final-Project
Deep Learning Final Project: Built and trained Stacked CNN AutoEncoder and Deep CNN AutoEncoder based on STL-10 dataset
Judithcodes/energy-harvesting
Summer research project at TIFR. Designing an algorithm for optimal packet scheduling with energy harvesting transmitter and reciever.
Judithcodes/ErrorAnalysisForDiffCodes
Investigated the effect of number of receivers on the bit error rate for a MIMO communication system which use differential space time encoding.
Judithcodes/evolutionary-sensors-positioning
An evolutionary approach for positioning multiple wireless sensors to allow simultaneous communication on the same frequency and at the same time.
Judithcodes/LSTM_Anomaly_Detector
A try to autoencode an LSTM to do anomaly detection
Judithcodes/maximum-number-of-retransmissions
Maximum number of transmission attempts between smart meters and aggregators in a spectrum sharing scenario in a smart grids
Judithcodes/OCD_sim
Simple massive MU-MIMO system simulator for Optimized Coordinate Descent (OCD)
Judithcodes/OMP_Dict
Use of different dictionaries on the OMP algorithm for DVBT2 channel estimation
Judithcodes/one-bit_massive_MIMO
Numerical routines for the computation of the achievable uplink throughput with PSK/QAM for a one-bit quantized massive MIMO system with a MRC/ZF receiver.
Judithcodes/Piezo-Energy-Harvesting-Board
Piezo energy harvesting board designed around the LTC3588 IC
Judithcodes/SVM-CNN
A feature extractor based on Python 3, Tensorflow and Scikit-learn created in order to improve the accuracy of SVM to classify MNIST dataset fast and with more accuracy.