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hybridprecodingmassivemimo

This project contains MATLAB codes for the paper: L. Liang, W. Xu, and X. Dong, "Low-complexity hybrid precoding in massive mulituser MIMO systems," IEEE Wireless Communications Letters, vol. 3, no. 6, pp. 653-656, Dec. 2014.

image-classification-deep-neural-networks-groceries

Image classification using three different convolution deep learning neural networks

image-classification-rnn

Classify MNIST image dataset into 10 classes. Build an image classifier with Recurrent Neural Network (RNN: LSTM) on Tensorflow.

improving-user-association-in-hd-wlans-using-machine-learning

Code for my bachelor's thesis

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

intelligent-model-of-communication-system-simulation-based-on-auto-encoding-deep-learning-

Used a Generative Adversarial Network(GAN) to simulate a optical communication system; Applying auto-encoding deep-learning method to build an Intelligent model of Communication system in order to improve its information rate and symbol coding method; laying a good foundation for the development of intelligent fiber communication systems;

intelligent-video-analytics-with-nvidia-jetson-and-microsoft-azure

A repository demonstrating an end-to-end architecture for Intelligent Video Analytics using NVIDIA hardware with Microsoft Azure

intro-to-convolutional-neural-networks

Source Code for 'Introduction to Convolutional Neural Networks' by Nemanja Milosevic

intro-to-machine-learning

Introduction to Machine Learning

introduction-to-artificial-intelligence-machine-learning

introduction-to-machine-learning-1

This repo will house all our course material and code snippets from the Introduction to Machine Learning Class

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"

iot-lora-demo

iotweathersensorsanalysis

Proposed "An Extended IoT Framework" learning part is presented with a use case on weather data clustering analysis. Sensor faults and anomalies are determined using K-means clustering (using scikit-learn)

ipsw-rfi

IPSW 2019 work

iris-data

EXPLORING THE IRIS DATA SET

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"

judithcodes.github.io

A simple baking site created using bootstrap(not yet complete)

judithnjoku.com

A sample website made with bootstrap

k-means

Kmeans algorithm implementation

k-means-clustering

Exercise on K-Means Clustering using Scikit-Learn

kalman

Adaptive Kalman filter in Golang

kalman-filters

Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, one of the primary developers of its theory.

kalman_filtering_for_nonlinear_estimation

keras-adversarial-autoencoders

Experiments with Adversarial Autoencoders using Keras

keras-oneclassanomalydetection

[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.

keras_sklearn

Combination of Keras CNN with Scikit-learn classifiers.

kmeans

KMeans Algorithms applied

kmeans-algorithm

Here I have uploaded two programmes, the first one named KMeans uses the sklearn library to implement a KMeans algorithm.Kmeans_scratch is implementation of kmeans from scratch.

kmeansamesize

Applying a modified K-means algorithm with each cluster having the same size