FIND Technologies Inc. (a Canadian company that focuses on detecting signatures emitted by organic and inorganic materials) is offering a $50,000.00 prize for the development of a signal analysis algorithm that can identify and categorize 1,500 data sets into 3 categories at an accuracy of +95%.

Full details can be found here: The Challenge

Back in March, when I traveled to ICASSP 2010, I was fortunate to assist to Ronald Schafer’s plenary talk. Since then, I have been trying to get a copy of it but I was told to wait for it to be posted on IEEE TV. It took a little longer than what I expected but finally it appeared a few weeks ago:

I think the presentation is excellent. It not only draws from Ron Schafer’s huge experience (see his bio at HP Labs and Wikipedia) and his renown teaching ability, but it also manages to cover a well-balanced presentation of the history of DSP (my favorite part), his view of the future and the technological importance of DSP.

As a small trivia, at around the 15 minutes mark, there is a mention in the video to an early publication describing the discrete-time convolution (is this the first time discrete-time convolution was published?). I was surprised to see in the list of editors (and also contributing authors) for the book the name of Ralph Phillips. This is because he is my great-great-great academic grandfather (I’m interested in my academic genealogy and had been able to trace it way back to the 14th century thanks to the help of the Math Genealogy Project).

The other day, I was taking a look at the latest list of the ten most read articles in the IEEE Journal of Selected Topics in Signal Processing , the IEEE Signal Processing Letters and the IEEE Transactions on Signal Processing. The lists have a notable number of papers on Compressive Sensing (or also called Compressive Sampling). This means that this is perhaps the hottest research topic in signal processing these days.

Because of this, I set myself to write a post to explain the basics of this relatively new technique. Luckily, I found publicly available these excellent lecture notes by Richard Baraniuk at the IEEE Signal Processing Magazine. For those who want an overview, the first page should suffice to get that, but I’d recommend to read it all. Also, there is a short tutorial by Michael Lamoureux that works as a nice complement to Baraniuk’s lecture notes.

Finally, there is a blog, called the Nuit Blanche blog, that is mostly dedicated to compressive sensing, and the very complete and useful webpage on compressive sensing resources at Rice University.

Enjoy.

Earlier this summer I gave a talk at RIT’s Summer Math Institute. This is a venue for STEM (science, technology, engineering, and mathematics) University and High School faculty to interact. One of the goals is to show to High School teachers how the concepts they teach are used in many of today’s technologies. So, my presentation was about explaining how most of what we do in DSP revolves around the simple operation of accumulating the multiplication of two sequences of numbers (plus complex numbers and trigonometry):

I think it is a nice way of introducing the basics of Digital Signal Processing to a general audience.

A couple of posts ago, I wrote about how DSP is a technology behind most of today’s technologies and advances. I also mentioned briefly the importance of volunteers for the IEEE. This post is closely linked with these two concepts.

As I mention then, the article “Signal Processing Inside”, inspired me to create this blog as a way of promoting the idea of “Signal Processing Inside”. It turned out that, after a couple twists of destiny, the blog led me into becoming an Associate Editor for the IEEE Signal Processing Magazine. Here, my role is to manage a permanent column called “In the Spotlight”. The column’s idea is to take news appearing in the mainstream media and present a technical discussion of the signal processing related to the news. For example, we have covered the recent (or maybe still current) worldwide financial crisis (by discussing signal processing methods to predict the evolution of stocks), or the H1N1 influenza outbreak (the topic was the study of the virus genome). We have also covered more technical topics such as the signal processing done at the Large Hadron Collider, part of the hardware installed in the last servicing mission to the Hubble space telescope and brain-computer interfaces. My role is that of deciding on the topics to be covered (in most of the cases), invite the authors and manage the writing of the article. For me, this has been a great source of personal satisfaction because I never imagined back when I was an undergraduate student, enjoying reading this magazine, that one day I would be managing an article in every issue. More importantly, I have learned a lot of things I didn’t know. So, although the time I dedicated to the column was one of the reasons I couldn’t post more often in this blog, this time will now pay off because I will discuss more signal processing inside topics in future posts here.

Finally, if you are interested in learning more about these articles and other columns in the IEEE Signal Processing Magazine, follow this link.

Submission of Camera Ready Papers due October 20, 2010.

http://www.icassp2011.com

At the time I was a postdoc at The University of Maryland, my mentor, Prof. K. J. Ray Liu, was Editor in Chief of the IEEE Signal Processing Magazine. As such, he wrote a number of very good columns. One of the best ones is “Signal Processing Inside”

The main point of the article is to highlight how Signal Processing as a technology does not get the recognition it deserves from society, simply because it is a “phantom technology”, working from behind the scenes to make most of modern day advances work. The article highlights how other industries and companies (e.g. Intel) face the same problems. But, unlike these industries and companies, the Signal Processing community per-se has not the resources to mount very expensive advertising campaigns. So, as the article says, it’s up to us, the Signal Processing community, to help ourselves and work for this technology to be broadly known.

In my case, this column has made a big influence in many of the ventures I do. One example is this blog, because when I thought about it, I wanted to be a tool to promote the impact that DSP has on our world. Ironically, it has influenced other activities I have been doing that had prevented me for posting more often.

In any case, I believe that “Signal Processing Inside” is a must read for anybody in the DSP community. If you like it, you should also read “Volunteers“.

The 2010 International Conference on Image Processing (ICIP) will take place in Hong Kong, September 26-29, 2010.

http://www.icip2010.org/

I will likely have some post coming up that were delayed due to my long period of silence. This post falls under this category.

Some time ago, one student pointed me to this video of a talking piano. The video is in German but the piano talks in English (the subtitles in the video help to understand what the piano says).

The details of the video explain that the procedure to get the piano to talk started with a recoding of a child. The creator of the talking piano calculated some kind of spectrogram of the speech and then translated the time-frequency information in the spectrogram into sequences of notes played in the piano. One interesting thing to note here is that typical spectrograms, based on the Fourier Transform, will give linearly separated frequencies, but the frequencies generated from the piano keys are logarithmically separated. Maybe using wavelets would have been better, but there is no information if this was the case. Another interesting thing to note is that the piano implements parts of the processing done at a vocoder or also at a sub-band coder.

It has been more than a year since I last published in this blog. The fact is that life had taken me through the busy life of a tenure-track faculty, plus other activities I’ll be posting about in the future. Nevertheless, I have been thinking about reviving the blog, only that this time I may be forced to make short posts, something longer than twitter but maybe shorter of what I used to. So, stay tuned…