CS: Around the blogs in 80 hours, Compressive Phase Contrast Tomography, Wideband Spectrum Sensing at Sub-Nyquist Rates

First, we have some blog entries:

• Piotr: Geometry @ Barriers
• Image Sensors World: Caeleste on X-Ray Photon Counting Sensors
• Andrew: Data Stream Algorithms slides
• Bob: Post-doc opportunity at INRIA
• Frank: Entropy of exponential families
• Terry: A first draft of a non-technical article on universality
• Hal: Manifold Assumption versus Margin Assumption

Then, the ONR just set a challenge on ideas related to Compressive Sensing in Urban Warfare. How are these challenges any different from your usual RFPs ? I don't know.

The day before yesterday, we talked about Jacket being used in the context of a reconstruction. Today this GPU based reconstruction with Jacket is part of a larger undertaking as featured in: Compressive Phase Contrast Tomography by F. R. N. C. Maia, A. MacDowell, Stefano Marchesini, H. A. Padmore, D. Y. Parkinson, Jack. Pien, Andre Schirotzek, and C. Yang. The abstract reads:

When x-rays penetrate soft matter, their phase changes more rapidly than their amplitude. Interference effects visible with high brightness sources creates higher contrast, edge enhanced images. When the object is piecewise smooth (made of big blocks of a few components), such higher contrast datasets have a sparse solution. We apply basis pursuit solvers to improve SNR, remove ring artifacts, reduce the number of views and radiation dose from phase contrast datasets collected at the Hard X-Ray Micro Tomography Beamline at the Advanced Light Source. We report a GPU code for the most computationally intensive task, the gridding and inverse gridding algorithm (non uniform sampled Fourier transform).

On the acquisition side, we have: :Wideband Spectrum Sensing at Sub-Nyquist Rates by Moshe Mishali, Yonina Eldar. The abstract reads:

We present a mixed analog-digital spectrum sensing method that is especially suited to the typical wideband setting of cognitive radio (CR). The advantages of our system with respect to current architectures are threefold. First, our analog front-end is fixed and does not involve scanning hardware. Second, both the analog-to-digital conversion (ADC) and the digital signal processing (DSP) rates are substantially below Nyquist. Finally, the sensing resources are shared with the reception path of the CR, so that the lowrate streaming samples can be used for communication purposes of the device, besides the sensing functionality they provide. Combining these advantages leads to a real time map of the spectrum with minimal use of mobile resources. Our approach is based on the modulated wideband converter (MWC) system, which samples sparse wideband inputs at sub-Nyquist rates. We report on results of hardware experiments, conducted on an MWC prototype circuit, which affirm fast and accurate spectrum sensing in parallel to CR communication.