Bayesian analysis of square-rooted values
Abstract
This is a pair of Jupyter notebooks developing a second-order-approximation square root decoder, using a Bayesian approach to interpreting detector values. The square root decoder improves residual error from ~0.24DN RMS to ~0.013DN RMS in a typical application. The Jupyter format allows reproduction and numerical experiment for other applications. One notebook shows the method's derivation and verification; the other shows application to a particular data set.
- Publication:
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Zenodo
- Pub Date:
- DOI:
- 10.5281/zenodo.6672640
- Bibcode:
- 2022zndo...6672640D
- Keywords:
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- Python Jupyter square-root coding