For the RHESSI satellite we develop an algorithm to reconstruct X-ray images of solar flares.
Technologies
Compressed Sensing, Quadratic programming, C#, IDL
Objective
Development of image reconstruction algorithms which take noisy X-ray measurements of a solar flare as an input, and output an image of the original X-ray emission of the solar flare.
Project status
Results have been shown at several international conferences. A working version of our new algorithm is currently being published, with above average reconstruction quality and speed. A scientific publication is in the making.
Project Information
Execution | |
Collaboration | |
Duration | 1.5 years |
Team | Simon Felix, Roman Bolzern, Dr. Marina Battaglia, Prof. Dr. André Csillaghy |
Project details
- Type
- Research project
- Topics
- Data Science und Engineering, Data science and engineering, Computer science and data science
- University
- FHNW School of Computer Science / Institute of Data Science
- Partner
- NASA Goddard Space Flight Center
- Funding
- NASA Goddard Space Flight Center
- Running time
- 1.5 years
- Management
- Simon Felix
- Team
- Roman Bolzern
Dr. Marina Battaglia
Contact us
Simon Felix
Research Associate at the Institute for Data Science FHNW
- Phone
- +41 56 202 76 89 (Direct)
- simon.felix@fhnw.ch
Prof. Dr. André Csillaghy
Head of FHNW Institute for Data Science
- Phone
- +41 56 202 76 85 (Direct)
- andre.csillaghy@fhnw.ch
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- Institute
- Institute of Data Science
- Research field
- Information Processing
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- Institute of Data Science
- Research field
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SySTEM2020: Connecting Science Learning Outside The Classroom
Research participant recruitment, data collection and mapping STEAM initiatives in Switzerland.
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IRIS Big Data
Machine learning methodology to detect, analyse and possibly predict solar flares from data provided by NASA's space telescope IRIS.
- Institute
- Institute of Data Science
- Research field
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