https://github.com/zimmerrol/rcp_spatio_temporal
Prediction spatio-temporal dynamics using Reservoir Computing
https://github.com/zimmerrol/rcp_spatio_temporal
biophysics echo-state-networks esn machine-learning reservoir-computing
Last synced: about 1 year ago
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Prediction spatio-temporal dynamics using Reservoir Computing
- Host: GitHub
- URL: https://github.com/zimmerrol/rcp_spatio_temporal
- Owner: zimmerrol
- Created: 2017-02-25T18:08:00.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2018-05-02T18:52:35.000Z (about 8 years ago)
- Last Synced: 2025-02-09T08:16:53.067Z (over 1 year ago)
- Topics: biophysics, echo-state-networks, esn, machine-learning, reservoir-computing
- Language: PostScript
- Homepage:
- Size: 150 MB
- Stars: 6
- Watchers: 2
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: readme.md
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README
# Bachelor Thesis of Roland Zimmermann
This repository contains the entire source code, the numerical results, generated images and illustrations as well as the .tex documents used writing the bachlor's thesis, written by Roland Zimmermann at the Max-Planck-Institute for Dynamics and Self-Organization in the group of Prof. Dr. U. Parlitz and the Georg-August-Universität Göttingen. The thesis deals with the problems of prediction spatio-temporal (chaotic) dynamics using Reservoir Computing (Echo State Networks).
## License
All content of this repository (with the exception of specially marked files) is created solely by Roland Zimmermann. The reuse of the code, ideas or passages of the text is allowed only if the work is correctly quoted and the original authorship is highlighted.
## evaluation
This folder contains python scripts to generate the images which are presented in the final thesis.
## paper
This folder contains the .tex code of the internship report and the final thesis. Futhermore, the subfolder src contains the commented and documented python source code which has been used writing the thesis.
## src
This folder contains all the source code which has been written writing the thesis. Many functions and scripts were not used in the end due to bad performance or other problems. This files are not entirely commented. Therefore, one should rather read the code written in paper/src. This folder here can just be used as a archive of different methods of the ESN framework.