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breast-cancer-diagnosis-using-machine-learning

Machine learning is widely used in bioinformatics and particularly in breast cancer diagnosis. In this project, certain classification methods such as K-nearest neighbors (K-NN) and Support Vector Machine (SVM) which is a supervised learning method to detect breast cancer are used.

breast-cancer-prediction

Supervised Learning Model to predict breast cancer

breast-cancer-risk-prediction

Classification of Breast Cancer diagnosis Using Support Vector Machines

breast-cancer-study

broadband_fewbit

The codes for the paper "Channel Estimation in Broadband Millimeter Wave MIMO Systems with Few-Bit ADCs"

cakemaker-portfolio

a mock portfolio for a cake baker

cancer_treatment_prediction

Cancer treatment prediction using clinical data

captain-sim

Underwater Simulator + CAPTAIN and SPA implementations.

castalia

An OMNeT-based simulator for low-power wireless networks such as Wireless Sensor Networks and Body Area Networks

cau_wirelessmobilecommunication

중앙대학교 컴퓨터공학부 최현경의 첫 안드로이드 아두이노도전기

channel-estimation

Simulates an FBMC and OFDM transmission over a doubly-selective channel. Allows to reproduce all figures from "Doubly-Selective Channel Estimation in FBMC-OQAM and OFDM Systems", IEEE VTC Fall, 2018

channel-estimation-based-on-dnn

graduation project by Guanxiong Shen, Heriot-watt University

channel-estimation-examples

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.

channel-power-allocation-802.22

matlab codes_Di Li and James Gross, Distributed TV Spectrum Allocation for Cognitive Cellular Network under Game Theoretical Framework Proc. of the IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN'12) 2012

channelnet

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

chemspot

ChemSpot is a named entity recognition tool for identifying mentions of chemicals in natural language texts, including trivial names, drugs, abbreviations, molecular formulas and IUPAC entities. Since the different classes of relevant entities have rather different naming characteristics, ChemSpot uses a hybrid approach combining a Conditional Random Field with a dictionary. ChemSpot is released under the Common Public License 1.0.

cluster-analysis

An introduction to Cluster Analysis and the K-Means clustering technique.

clustering-algorithms

Spectral, Agglomerative and Kmeans Clustering Implementation

clustering_seminar

Algorithms for KMeans, Hierarchichal clustering, EM and DBSCAN

cnn

Convolutional ANN using RadioML data

cnn-for-image-classification

CNN image classifier for Malaria detection using cell images

cnn-rtlsdr

Deep learning signal classification using rtl-sdr dongle

cnn-svm

An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classification

cnn-svm-classifier

Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine

cognitive-radio

Simulation Study of Double Threshold Energy Detection Method for Cognitive Radios

cognitive-radio-1

MATLAB codes for cognitive radio which we used through the year

cognitive-radio-spectrum-sensing

cognitive_radio_ml

Using Machine Learning for Spectrum Awareness

cognitive_radio_networks

Software Defined Radio - Development Codes