Adventures in Signal Processing and Open Science

Month: June, 2014 update

I mentioned the Episciences project the other day in Scientific journals as an overlay. In the meantime I have tried to contact the people behind this project and The Open Journal, apparently without any luck.

I went and checked the Episciences website yesterday and it actually seems that they are moving forward. They changed the page design completely and there is now a button in the upper right corner to create an account and log in. I took the liberty of doing so to have a look around. I was able to create an account, but is just about it so far. The site still seems quite “beta” – I was not able to save changes to my profile and I cannot yet find anywhere to submit papers. It is nice to see some progress on the platform and I will be keeping an eager eye on it to find out when they will go operational.

Compressed Sensing – and more – in Python

Compressed Sensing – and more – in Python

The availability of compressed sensing reconstruction algorithms for Python has so far been quite scarce. A new software package improves on this situation. The package PyUnLocBox from the LTS2 lab at EPFL is a convex optimisation toolbox using proximal splitting methods. It can, among other things, be used to solve the regularised version of the LASSO/BPDN optimisation problem used for reconstruction in compressed sensing:

\underset{x}{\mathrm{argmin}} \| Ax - y \|_2 + \tau \| x \|_1


Heard through Pierre Vandergheynst.

I have yet to find out if it also solves the constrained version. Update: Pierre Vandergheynst informed me that the package does not yet solve the constrained version of the above optimisation problem, but it is coming:

\underset{x}{\mathrm{argmin}} \quad \| x \|_1 \\ \text{s.t.} \quad \| Ax - y \|_2 < \epsilon

Scientific journals as an overlay

There is an update on this post in update

In many of my posts since I started this blog, I have been writing about open peer review. Another topic related to open science that interests me is open access (to scientific papers). Part of open access in practice is about authors posting their papers, perhaps submitted to traditional journals, to preprint servers such as arXiv. This is used a lot, particularly in physics and mathematics.
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