Paper * “Generation and Analysis of Constrained Random Sampling Patterns” * was accepted for publication in Springer journal “Circuits, Systems & Signal Processing”. Preprint is available for viewing in **arXiv** server: http://arxiv.org/abs/1409.1002 .

# ‘melancholia’ is available to download

A small side-project, **‘melancholia’** module, is available to download . Python module **‘melancholia’** is able to print NumPy arrays into a variable or a file in a nice, human-readable way.

The module is available on GitHub , module’s documentation is here .

Please take a look on two examples of NumPy arrays printed with **‘melancholia’**: 2-dimensional arrays and 1-dimensional arrays . User decides about numbers format, delimiters, line wrapping etc.

Here are some examples of using **‘melancholia’** in Python programs.

# New reconstruction algorithm implemented

Iterative Reweighted Least Squares (IRLS) algorithm is added to RxCS software. This implementation of the IRLS allows to solve an l1 optimization problem using an l2 solver. You can find the IRLS algorithm implemented in Python on GitHub. An example of using IRLS to solve an underdetermined system is here.

A wrapper which employs IRLS to solve a compressed sensing problem is also availabe on GitHub, an example of usage is here.

# Reproducible materials for ‘Frequency Selective Compressed Sensing’ paper

Reproducible materials for “Frequency Selective Compressed Sensing” are available here . Reproducible research scripts are available on GitHub .

# Inverse Discrete Hartley Transform Module

A new module is present in RxCS software: ** Inverse Discrete Hartley Transform **. You can find the module on RxCS’s GitHub page , an example of how to use the module is also available on GitHub.

# Workshop on Compressed Sensing in Wireless Communication

Workshop on Compressed Sensing in Wireless Communication will be held at the European Wireless 2015 conference . You can find the workshop’s website here.

# Paper submitted to IEEE Signal Processing Letters is now available on arXiv.org

Our paper “Frequency Selective Compressed Sensing” submitted to IEEE Signal Processing Letters is now available on arXiv.org

# Paper submitted to IEEE Signal Processing Letters

Paper “Frequency Selective Compressed Sensing” was submitted to IEEE Signal Processing Letters. The paper will be soon available in arXiv, reproducible research Python scripts will be available on the website in a couple of days.

# One more example in RxCS

An example of using **RxCS** module with ** Kernel Recursive Least Squares algorithm ** is added to RxCS toolbox . You can find the example on GitHub , or directly in the toolbox in ** examples/auxiliary** dictionary.

# New example of using RxCS

A new example of using RxCS software is added. In this example a L1 reconstruction (regularized regression) module is explained. You can find the example here .