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Monday, March 09, 2009

CS: Compressive Data Acquisition using LabView, CS and biology, and NMF.

Today, we mostly have new potential area of investigation where CS might be of interest.


First, we have Compressive Data Acquisition using National Instrument's LabVIEW. This is a first. The document begins with:

Compressive Data Acquisition

This Compressive Data Acquisition LabVIEW program presents a signal reconstruction algorithm from a set of single random (scalar) measurements, where the signal is sparse in some transform domain. Each measurement or observation represents a random projection of the signal onto a single scalar value. By applying Discrete Radon Transform techniques, the original signal can be reconstructed from these random sampled measurements. However, this requires a very large set of measurements which defeats the purpose of compressive data acquisition. To acquire the wideband data below the Nyquist frequency, a rank order filter is applied in the sparse transform domain to extract the most significant components.




In this week-end's Hackaday posting, we were introduced to a way for performing Remote Image Processing in Javascript. Why is this interesting ? well we have a dumb sensor serving information over the web. A web browser on the other end does a simple operation and raise an alarm. It pretty much is the model we use in compressive sensing. If the camera were to be random lens imager, I think it could be an interesting application.

Olgica Milenkovic has a poster on her research linking compressive sensing and biology. it is here. I like the sense of smell part of the poster.

Bob Plemmons hints that Compressive Sensing maybe of help in his NMF and Space Situational Awareness work (see the last slide).

2 comments:

  1. Hi Nuit Blanche,
    Thanks for referring to my CS postint using LabVIEW. I am the original author and developer of this algorithm.

    I hope to find more time to work on this fascinating topic.

    Keep up the great job. I am now a fan of your blog.

    Regards,
    -- Lalo

    ReplyDelete
  2. Hello Lalo,

    Can you contact me by e-mail, I'd like to talk about you onthe reconstruction algorithm you have developed.

    Cheers,

    Igor.

    ReplyDelete