Using machine learning and neural networks to efficiently search for pulsars in processed radio telescope data.
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Updated
Jan 30, 2021 - Python
Using machine learning and neural networks to efficiently search for pulsars in processed radio telescope data.
Toolkit for working with astronomical radio transients in the SIGPROC Filterbank format in Julia
Senior Thesis on Applying Neural Networks in Pulsar Identification
This is an experimental python script predicts the Time of Arrival (TOA) and gate boundaries for a pulsar for gated imaging applications. Currently, the code is tailored for GMRT observations
Detecting Radio Signals with Spectral Structure
Simple isolated pulsar timing tools geared towards high energy astrophysical data
HarvardX DataScience Professional Certificate - Final Capstone IDV Project - Predicting Pulsars using machine learning algorithms. In this project we determine which machine learning algorithm has the highest prediction accuracy in predicting Pulsars.
Machine Learning projects for Data-Driven Astronomy
Mean of a Stack of FIT file to detect pulsar in space
This project focuses on classifying pulsar stars using the Support Vector Machine (SVM) algorithm, a powerful method in the realm of supervised learning. The goal is to automate the identification process of pulsar stars from candidates collected during surveys, based on predictive modeling.
Supplementary material for the paper "The UTMOST pulsar timing programme I: Overview and first results".
NenuPlot is a PSRFITS merging (in time and frequency) and cleaning pipeline
Repository to host Artificial Intelligence projects, a third year unit @FEUP. Made in collaboration with @EdgarACarneiro and @jflcarvalho.
Study of different machine learning algorithms for the detection of Pulsars. Final project for the Bachelor's degree subject Machine Learning.
Match single-pulse detections to known sources, such as canonical pulsars or Rotating Radio Transients.
possibly a new mechanic installation
How would you correctly classify pulsars from a dataset that consists mostly of astronomical noise? In this project, I construct 5 machine learning models and analyze their performance to find a winner.
Convert uGMRT raw data files to sigproc-filterbank format.
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