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Section: Publications & Resources

In this series, we introduce topics outside of the signal processing world from which we believe signal processing researchers and practitioners can benefit.

Section: Publications & Resources

The Machine Learning for Signal Processing Technical Committee (MLSP TC) is involved with activities that support the use of Machine Learning techniques for Signal Processing problems. The scope of this TC is fairly wide, ranging from traditional machine learning and pattern recognition, to approaches that combine material from both disciplines. Under the scope of the MLSP TC we find areas such as source separation, graphical and kernel methods for time-series, Bayesian non-parametrics, and matrix and tensor factorizations among many more.

Section: Publications & Resources

During the last couple of months, a few new Signal Processing and Machine Learning contests were initiated. Some of the ongoing ones with a strong relation to Signal Processing include: From the domain of Signal Processing for cartography there is a Kaggle contest asking to predict the forest cover type (the predominant kind of tree cover) from strictly cartographic variables (as opposed to remotely sensed data).

Section: Publications & Resources

The signal processing chapter of the IEEE Singapore Section was founded by me in 1989 with over twenty petitioners. It was established first as a special interest group in 1988 and subsequently in 1989 it was upgraded to the chapter status.

Section: Publications & Resources

A team led by Stanford electrical engineers has compressed a completely sequenced human genome to just 2.5 megabytes – small enough to attach to an email. The engineers used what is known as reference-based compression, relying on a human genome sequence that is already known and available. Their compression has improved on the previous record by 37 percent. The genome the team compressed was that of James Watson, who co-discovered the structure of DNA more than 60 years ago

Section: Publications & Resources

Bing Hu, (University of California, Riverside) “Mining Time Series Data: Moving from Toy Problems to Realistic Deployments” (2013) Advisor: Eamonn Keogh Data mining and knowledge discovery has attracted a lot of research interest in the last decade.

Section: Publications & Resources

 Yingying Zhu (University of California Riverside) “Towards Sparse Modeling of Multi-object Interactions in Video” Advisor: Amit K. Roy-Chowdhury In this dissertation, we develop intelligent methodologies for the modeling and recognition of activities in continuous videos.

Section: Publications & Resources

Please refer to the following webpage for the latest updates on upcoming conferences in Signal Processing. http://www.signalprocessingsociety.org/conferences/upcoming-conferences/

Section: Publications & Resources

Now IEEE SPS has built a streamlined mechanism for employers to add a job announcement by simply filling in a simple job opportunity submission Web form at the related TC section pages. To submit job announcements for a particular Technical Committee, the submission form can be found by visiting the page below and clicking on a particular TC. A link for the form can be found in the sidebar menu of the TC pages.

Section: Publications & Resources

128 Signal Processing Society Members Elevated to Senior Member The IEEE Signal Processing Society (SPS) is honored to announce the elevation of 128 of its members to the grade of IEEE Senior Member. These members have demonstrated outstanding professional performance, exhibited professional maturity through long-term experience, and established themselves as leaders in their respective IEEE-designated fields of interest. Senior Member is the only membership grade that is eligible to be nominated for IEEE Fellow.